TechOnion

The Big Short Rib: How Klarna Turns Your Midnight Pizza Order into Wall Street’s Hottest Asset Class

Simba

-

May 20, 2025

The Big Short Rib: How Klarna Turns Your Midnight Pizza Order into Wall Street’s Hottest Asset Class

In what financial historians will surely record as late-stage capitalisms’ magnum opus, your regrettable 1 AM pepperoni pizza Dominos order can now be financed over three convenient monthly installments via Klarna, bundled with thousands of other poor financial decisions, and sold to institutional investors who once considered mortgage-backed securities too risky. Welcome to 2025, where your drunk food cravings have been transformed into an exciting new asset class that Harvard MBAs are calling “the ultimate fusion of tech disruption and questionable life choices.”

Deliveroo, the food delivery platform that somehow convinced us all that paying a £4.99 (About $7 depending on what Uncle Donald Trump decides for the world economy) fee for lukewarm restaurant food delivered by a cyclist who judges your order is a good idea, has partnered with Klarna to offer Buy Now, Pay Later services on all orders. The groundbreaking innovation allows customers to finance their doner kebabs and curries with the same financial instrument previously reserved for Pelotons and Apple iPhone upgrades that nobody needed.¹

The Three-Month Pizza Plan: Amortizing Your Regrets

Under Deliveroo’s revolutionary payment model, customers can choose to pay for their food immediately (BORING!), within 30 days (still fairly responsible), or split the cost into three monthly installments for orders over £30 (about $40 bucks – financial self-sabotage with a side of fries!).² The third option has quickly become a favorite among young professionals who want to maintain the lifestyle of someone earning twice more than they actually do.

“It’s about empowering consumers with flexibility,” explained Carlo Mocci, chief business officer at Deliveroo UK, while carefully avoiding the phrase “enabling poor financial decisions.” “We’re giving customers more choice and more flexibility with a safe, secure way to pay online”.

The partnership has been praised by those who believe the primary barrier to happiness is the inability to finance a bucket of chicken hot-wings over a fiscal quarter. Critics, meanwhile, have called it “the dumbest thing since NFT restaurants” and “a concerning development in our society’s relationship with both debt and saturated fats.”

Personal finance expert Tara Flynn of MoneySavingExpert cut directly to the chase: “If you’re considering buying your takeaway now and paying for it later… don’t. Getting yourself into debt over a meal that’s gone in 15 minutes isn’t worth it”.³ But why listen to financial experts when you can instead listen to the voice in your head at 12 midnight saying “You deserve this Tandoori feast NOW, and deal with the consequences LATER”?

From Your Stomach to Wall Street: The Miracle of Modern Finance

Here’s where the ordinary becomes extraordinary. Klarna isn’t just holding onto your pizza debt like a nostalgic memento. No, they’re packaging it up with thousands of other food debts and selling it to hedge funds and institutional investors through the miracle of securitization – that is where they make their REAL money!⁴

According to recent reports, Klarna is selling most of its British BNPL loans to American hedge fund Elliott, freeing up an estimated $39 billion for new loans.⁵ This means your outstanding £36.50 Meat Feast Extravaganza payment is now sitting in the investment portfolio of a US pension fund manager who’s never experienced the existential crisis of adding extra cheese at a Deliveroo checkout.

The structure works similarly to the Domino’s Pizza securitization model, where the company created a special purpose vehicle (SPV) called “Domino’s Pizza Master Issuer LLC” into which it sold its revenue-generating assets.⁶ In Klarna’s case, the SPV might as well be called “The Repository of Questionable Midnight Cravings LLC,” where your three outstanding payments for chicken wings join forces with thousands of other fast food financing arrangements.

Meet the Pizza-Backed Security: Wall Street’s Tastiest Financial Innovation

Financial analyst Matthew Van Herzeele recently explained securitization on LinkedIn, describing how “bank and fund managers come together to create a special-purpose vehicle (SPV) to hold these assets banks need to unload”.⁷ In this case, the assets are the digital equivalent of IOUs scribbled on greasy napkins.

What makes food-backed securities particularly innovative is their unique risk profile. Unlike houses, which at least exist for decades, the underlying assets securing these loans have a half-life measured in minutes and an afterlife manifesting as indigestion and obesity. The collateral literally disappears down the customer’s esophagus before the first payment is due.

“It’s fascinating,” explained one Wall Street analyst who requested anonymity because his firm is currently underwriting several chicken-backed security offerings. “We’re essentially creating a financial instrument backed by assets that have negative value after consumption. It’s like securitizing hot air.”

The Tranches: From AAA Sushi to Subprime Nuggets

Just as with mortgage-backed securities, food debt is carefully sorted into risk tranches. At the top sit the AAA-rated sushi orders from affluent neighborhoods with perfect payment histories. In the middle are the BBB-rated pizza deliveries to young professionals who usually make their payments but occasionally need a reminder. And at the bottom are the high-risk, high-yield “subprime chicken nuggets” – the 3AM chicken orders to university dormitories that have a default rate coinciding precisely with student loan payment dates.

One hedge fund has reportedly created an algorithm that assigns risk scores based on not just the customer’s credit history but the specific food ordered. Thai food at 7 PM on a Wednesday? Low risk. Twelve chicken wings, three sides, and two milkshakes at 2:30AM on a Saturday? High risk but potentially high reward if they make their payments.

“The beauty of these securities,” explained a quantitative analyst at a major investment bank, “is that we can predict default rates based on topping choices. Pineapple on pizza correlates with a 23% higher risk of missed payments. It’s the financial equivalent of a red flag.”

The Curious Case of Chicken-Backed Liquidity

The market for food debt securities has grown exponentially since Deliveroo and Klarna first partnered in 2022. What started as a £5.6 billion market has expanded to roughly the size of Denmark’s GDP, driven by an insatiable appetite for both takeaway food and exotic financial instruments.

The key selling point for investors is diversification. As one portfolio manager put it: “Look, chicken wing demand is essentially recession-proof. People might stop buying homes during an economic downturn, but they’ll sooner cancel their health insurance than stop ordering takeout. That makes these securities surprisingly resilient.”

But not everyone is convinced. Sue Anderson from debt charity StepChange warned: “It’s a worrying development to see mainstream food delivery providers offering BNPL, especially at a time of such financial uncertainty for households”. Research shows those using BNPL are often already in financial difficulty, with a quarter of BNPL users having to borrow from other sources just to keep up with essential costs.

The 2027 Fried Chicken Financial Crisis: A Prediction

Financial experts are already gaming out scenarios for what some are calling “the inevitable fast food financial crisis.” As with any securitization boom, the key risk is mispricing of risk and contagion when defaults start rising.

“What happens when a recession hits and suddenly thousands of people can’t make payments on their three-month pizza plans?” asks one economist. “The SPVs start to fail, the securities lose value, and institutions that are overexposed to chicken-backed securities have to write down billions in losses. Then everyone acts surprised, as if financing consumable goods over multiple months wasn’t obviously problematic.”

Others point to the lack of regulation. “BNPL is not yet regulated, providers may not carry out effective affordability checks or prevent users from taking out multiple BNPL loans from different retailers they are unable to repay,” warns StepChange. This means someone could theoretically go on a tour of digital gluttony, financing a pizza via Deliveroo, a burger via Uber Eats, and a curry via Just Eat, all without any single provider knowing about the others.

In boardrooms across London and New York, risk committees are running stress tests on scenarios like “Widespread Sriracha Shortage” and “TikTok Trend Makes Cooking at Home Cool Again,” trying to calculate the potential downstream effects on their chicken-backed security portfolios.

The Fintech-Fast Food Industrial Complex

The unholy alliance between delivery apps, payment processors, and financial institutions represents what industry insiders are calling “the final frontier of financialization.” Having successfully monetized housing, education, healthcare, and even dating, the financial sector has finally figured out how to extract value from your desperate search for dopamine via deep-fried poultry.

David Sykes, chief commercial officer at Klarna, defended the practice: “We believe you should only pay for what you buy with no interest or fees, and it’s never been more important for consumers to have access to payment options which help them stay in control of their finances”. This statement came shortly after Klarna announced it was selling most of its British BNPL loans to American hedge fund Elliott, presumably because nothing says “helping consumers stay in control of their finances” like selling their debt to a hedge fund known for aggressive investment strategies.

A Klarna spokesperson further justified the model by explaining that “people have been paying for takeaways with credit cards and overdrafts for decades”, seemingly unaware that “other people made poor financial decisions in the past” isn’t typically considered sound financial advice!

The Pizza Default Swap: Coming Soon to a Bloomberg Trading Desk Near You

As the market matures, derivative products are inevitably emerging. Credit default swaps allowing investors to bet against pizza-backed securities are trading with increasing volume.⁸ Complex structured products with names like “Synthetic Collateralized Chicken Obligations” are being marketed to sophisticated investors looking to increase their exposure to the takeaway sector without the burden of actually owning debt backed by rapidly depreciating edible assets.

One trader described the appeal: “The beauty of these instruments is their short duration. With mortgages, you’re looking at 30-year terms. With car loans, maybe 5 years. But with chicken wings? The entire lifecycle from origination to final payment is just 60 days. The velocity of capital is incredible.”

This rapid turnover has created what some analysts are calling “the perfect perpetual motion machine of bad debt.” As soon as one cohort of tipsy customers finishes paying for their regrettable late-night food choices, another cohort is just beginning their own journey of financial self-sabotage, creating an endless supply of new debt to securitize.

The Future: Micro-Financed Mouthfuls

Industry insiders suggest this is just the beginning. Plans are reportedly underway to offer financing options on individual menu items, allowing customers to pay for the burger today but finance the fries over the next two weeks.

“We’re working on real-time bite-financing,” revealed one fintech executive who spoke on condition of anonymity because the technology is still in development. “Our AI can track exactly how much of the pizza you’ve eaten and adjust your payments accordingly. Eat a quarter of the pizza? Pay a quarter of the bill. The technology uses your front-facing camera to calculate consumption ratios with 97% accuracy.”

When asked about privacy concerns, the executive scoffed. “Privacy? You’re literally allowing strangers to bring food to your home based on an app that already knows your eating habits, address, and credit card details. You gave up privacy around the same time you started taking pictures of your meals for Instagram.”

As we contemplate a future where every french fry comes with its own amortization schedule, one can’t help but marvel at the innovative ways capitalism continues to extract value from increasingly mundane activities. The securitization of food delivery debt represents either the pinnacle of financial innovation or the absolute nadir of our collective decision-making, depending entirely on whether you’re selling these securities or buying that 1 AM pizza.

So what do you think? Is financing your takeaway over three months the height of modern convenience or a sign of impending financial doom? Have you ever used Klarna to buy food you couldn’t afford, or are you more of a “if I can’t pay for my pizza now, I don’t deserve pizza” purist? Perhaps you’re an institutional investor looking to diversify your portfolio with some spicy chicken-backed securities? Share your thoughts in the comments below, preferably before your next financed meal arrives.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Stack Over-Now-Underflow: The Tragicomic Tale of How AI Killed the Internet’s Sacred Developer Temple

AI
Featured

Simba

-

May 20, 2025

0

Stack Over-Now-Underflow: The Tragicomic Tale of How AI Killed the Internet’s Sacred Developer Temple

In what future tech historians will surely describe as the most predictable tech extinction since Blockbuster faced Netflix, Stack Overflow — the hallowed digital monastery where software programmers once gathered to both solve and create new programming problems—is quietly vanishing into the digital ether, leaving behind only the fading echo of “this question has been marked as duplicate” notifications.

Recent data reveals that Stack Overflow’s question volume has plummeted faster than a tech CEO’s principles during a US congressional hearing, with a devastating 25% reduction in user activity within just six months of ChatGPT’s release.¹ What began as a slow decline in mid-2020 has accelerated into what data scientist Theodore R. Smith, a top 1% Stack Overflow contributor, diplomatically calls an “alarming” drop in questions that continues into 2025.²

The Digital Murder Mystery Nobody Is Investigating

The prime suspect in this crime against developer community resources? AI coding assistants like GitHub Copilot, ChatGPT, and their increasingly smug algorithmic cousins who’ve never experienced the character-building trauma of being downvoted into oblivion for forgetting to use a semicolon.

“I haven’t opened Stack Overflow in months,” confessed one software developer on a Discord channel, where such admissions are becoming as common as “thoughts and prayers” tweets after a tech platform outage. The evidence is clear: developers are ghosting the platform that once served as their collective brain, preferring instead the instant gratification of AI assistants that never tell them to “Google harder” before answering.³

The irony hasn’t been lost on keen observers—these AI assistants were trained on the very knowledge base they’re now helping to destroy. It’s the digital equivalent of a child eating its parent, if that parent were composed entirely of JavaScript solutions and heated debates about tabs versus spaces.

The Autopsy Results Are In: Death By Convenience

What killed Stack Overflow wasn’t just ChatGPT’s uncanny ability to generate solutions faster than a human can type “How do I center a div?” It was the culmination of forces that were years in the making.

Stack Overflow’s notorious community tone—where newcomers faced a gauntlet of criticism that made Marine boot camp look like a pre-school graduation—certainly played its part. As one former user eloquently described it, “Stack Overflow’s community is the reason I stopped asking questions,” presumably before adding “also, the existential dread of realizing I’ll never truly understand regular expressions.”

By 2023, approximately 36% of developers were actively using AI assistants to understand coding errors and generate fixes.⁴ Fast forward to 2024, and that number skyrocketed to 63% of professionals incorporating AI into their regular workflows.⁵ Now, in our glorious 2025, industry analysts project that AI assistants will write as much as 90% of software code within a year—a statistic that should terrify anyone who has ever received an “I’ll fix it in the morning” Slack message from a developer.

The Promised Productivity Paradise

The tech industry’s love affair with AI coding assistants is fueled by impressive-sounding statistics that executives can’t wait to share during quarterly earnings calls. Research suggests that AI adoption provides a stunning 15-33% productivity improvement via successful pull requests.⁶ According to the DORA report, a 25% increase in AI adoption is linked to a respectable 2.1% rise in productivity, which is coincidentally the exact percentage increase in executive bonuses for implementing AI solutions.⁷

Microsoft, keen to remind everyone they’re not just about forced Windows updates anymore, reported that 77,000 organizations have adopted GitHub Copilot since its release in October 2021.⁸ Meanwhile, Y Combinator’s managing partner, Jared Friedman, revealed that a quarter of startups in their current cohort have codebases that are “almost entirely AI-generated,” which explains why they all seem to be solving the same three problems.

The Glorious Age of Copy-Pasta Engineering

Today’s modern developer workflow has evolved from “search Stack Overflow, copy code, modify slightly, pretend you wrote it” to the much more efficient “ask AI assistant, copy code, don’t bother understanding it, ship to production.” Progress, ladies and gentlemen!

Simon Lau, an engineering manager at ChargeLab, summed up the industry’s FOMO-driven adoption perfectly: “AI is something that helps us, and it is also helping our competitor as well, right? So if we are not utilizing this, we are not leveling the playing field with our competitor.” This profound statement captures the essence of modern tech strategy: do it because everyone else is, regardless of whether it makes sense, like wearing Allbirds to a VC meeting in 2019.

The benefits extend beyond mere productivity. Developers using AI tools reported improvements in “flow” (+2.6%), which is corporate-speak for “staring at the screen while the machine does the work,” and “job satisfaction” (+2.2%), likely due to having more time to perfect their coffee brewing techniques. Most impressively, they claim a 3.4% improvement in code quality, a statistic that conveniently ignores the 41% increase in bugs found in AI-generated code.

The Cannibal That Starves Itself

In the most delicious irony since Facebook became Meta about its own toxicity, AI coding assistants are devouring the very data sources that make them intelligent. As Stack Overflow questions decrease, the training data for future AI models diminishes, creating what ML engineer Ayhan Fuat Çelik eloquently calls “The Fall of Stack Overflow.”⁹

“With fewer questions about current programming problems being asked on the public internet, the training data for the coding assistants of tomorrow gets reduced,” explains one AI researcher, apparently unaware of the existential paradox this presents. “Ironically, the AI coding assistants of today are one of the main reasons for the fall of Stack Overflow and why people ask their questions in private to an AI.”

This creates a fascinating scenario where future AI models may need to be trained on the outputs of current AI models—a practice experts warn risks “model collapse,” where errors accumulate over generations, resulting in nonsensical outputs. It’s like a digital version of royal in-breeding, but instead of Habsburg jaws, we get AI that suggests putting your database credentials directly in your GitHub repository.

The Most Endangered Programming Species

Not all programming topics have suffered equally in this AI-driven extinction event. According to detailed analysis, questions about fundamental programming concepts (lists, dictionaries, loops) and data analysis tools (pandas, dataframes, SQL) have experienced the most significant declines.¹⁰

Meanwhile, topics related to operating systems and certain development frameworks like Next.js, .NET, and Azure have seen comparatively smaller decreases. This suggests that AI is better at handling straightforward coding tasks but still struggles with more complex, context-dependent challenges—much like entry-level developers after a three-month bootcamp who list “proficient in AI prompt engineering” on their LinkedIn profiles.

The Future: Hand-Coding Goes Artisanal

As we look toward 2040 and beyond, when researchers predict AI will fully replace software developers, one can’t help but imagine a dystopian future where writing code manually becomes an artisanal craft, like churning your own butter or using a paper map.¹¹

“I hand-code all my functions,” a hipster developer will say in 2035, adjusting their analog smartwatch. “The machines don’t understand the soul of a well-crafted recursive algorithm. Also, I don’t trust them after the Great Stack Overflow Knowledge Gap of 2028.”

Indeed, nearly 30% of software developers surveyed already believe their development efforts will be replaced by artificial intelligence in the foreseeable future. The remaining 70% were presumably too busy fixing AI-generated bugs to respond to the TechOnion survey.

The Developer Identity Crisis

Perhaps the most profound impact of this shift is psychological. For decades, developers have defined themselves by their ability to solve complex problems through code. Stack Overflow provided not just answers but a community and status system where reputation points served as a measure of one’s worth—the programmer’s equivalent of TikTok likes.

Now, as AI assistants eliminate the need to personally understand how code works, software developers find themselves in an existential crisis. “Am I still a developer if I’m just telling AI what to build?” asks one senior engineer on Reddit, before quietly updating his LinkedIn profile to “AI Workflow Optimization Specialist.”

This crisis extends to companies mandating AI tool usage without understanding their limitations. As one anonymous developer put it: “Under pressure to embrace AI, developers are growing frustrated by misguided mandates and are left to clean up any collateral damage”. In other words, executives want the 33% productivity gain but don’t want to hear about the 41% increase in bugs that comes with it.

The Vicious Circle of Knowledge Extinction

The most alarming aspect of Stack Overflow’s decline is how it creates a vicious cycle: fewer questions means less current knowledge being shared publicly, which means future AI models will be trained on increasingly outdated information. This, in turn, will produce AI assistants that generate obsolete code, forcing developers back to… well, not Stack Overflow, because it will be a digital ghost town populated only by bots asking each other about jQuery solutions in 2030.

Stack Overflow’s own 2024 insights admitted: “More people are reading than contributing,” which is a polite way of saying “developers are done engaging”.¹² It’s like a digital version of the tragedy of the commons, where everyone wants to benefit from community knowledge but nobody wants to contribute to it—especially when they can just ask ChatGPT-5 instead.

So what happens when all the smart humans stop sharing their knowledge publicly? When the next generation of programming languages and frameworks emerges, will there be enough human-generated solutions to train AI on? Or will we enter a dark age of programming where AI assistants confidently generate solutions that worked great in 2018 but are hopelessly obsolete for the challenges of 2030?

As we stand at this technological crossroads, one thing is clear: the developers who can still solve problems without AI assistance will be the digital wilderness guides of tomorrow—rare, valuable, and probably sporting magnificent beards while charging astronomical consulting rates that make current cloud computing costs look like pocket change.

So what do you think? Are you mourning the slow death of Stack Overflow, or celebrating your liberation from snarky comments about your “poorly formatted question”? Has your relationship with AI coding assistants evolved from skepticism to dependency? Share your existential coding crisis in the comments below—if you can still formulate a coherent thought without asking an AI assistant to generate it for you.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

The Great AI Energy Crisis: How Eric Schmidt’s ‘Underhyped’ AI Revolution Will Leave Us in the Dark

AI

Simba

-

May 20, 2025

1

The Great AI Energy Crisis: How Eric Schmidt’s ‘Underhyped’ AI Revolution Will Leave Us in the Dark

In a shocking twist that surprised absolutely no one with a fully functioning frontal lobe, former Google CEO Eric Schmidt took the TED 2025 stage last week to declare that artificial intelligence – the technology currently receiving more media coverage than oxygen and Donald Trump – is actually “underhyped.” Yes, you read that correctly. The man who helped steer one of the world’s largest tech companies believes we’re not talking enough about AI, in the same way that fish might not be talking enough about water.

Schmidt’s talk, delivered to an audience of head-nodding tech enthusiasts who would applaud a toaster if it had “AI-powered” in its name, argued that we are “drastically underestimating the scope and speed of the AI revolution”.¹ This from the man whose company once thought Google+ would be a Facebook killer.

When Machines Play Board Games Better Than Your Retirement Portfolio

The crux of Schmidt’s argument rests partially on AlphaGo’s legendary 2016 victory over Go champion Lee Sedol, which Schmidt frames as a watershed moment for artificial intelligence.² For the uninitiated (or those with actual hobbies like Chess), Go is an ancient Chinese board game with more possible configurations than there are atoms in the known universe. AlphaGo’s victory was indeed impressive – the AI made a move so unexpected that human experts initially thought it was a mistake.³

“What happened in this particular set of games was in roughly the second game, there was a new move invented by AI in a game that had been around for 2,500 years that no one had ever seen,” Schmidt gushed during his TED talk, conveniently glossing over the fact that Lee Sedol ultimately won one game against the machine.⁴

But here’s where our inner Sherlock Holmes starts twirling his metaphorical mustache. AlphaGo’s victory, while impressive, bears a suspicious resemblance to other carefully controlled AI demonstrations. Consider Meta’s recent Llama 4 controversy, where the company submitted a specially crafted, non-public variant called “Llama-4-Maverick-03-26-Experimental” to benchmark tests.⁵ When the actual public model was released, users reported “lackluster results” compared to the benchmark claims. One might reasonably ask: Was AlphaGo similarly “optimized” specifically for its match against Lee Sedol?

As one unnamed AI researcher who asked to remain anonymous because they “enjoy having a career” told us: “Winning at Go is impressive, but it’s also a closed system with perfect information. Real-world problems are messy. It’s like saying you’re ready for the Daytona 500 because you’re really good at Mario Kart.”

90 Gigawatts? Great Scott!

Perhaps the most glaring omission in Schmidt’s techno-utopian TED sermon was any meaningful discussion of the absolutely eye-watering energy requirements of his ‘underhyped’ AI revolution. According to recent projections, AI data centers could consume a staggering 90 gigawatts of power globally by 2028.⁶ For context, that’s roughly the equivalent of Denmark’s entire power consumption.⁷ Not a neighborhood in Denmark. Not a city in Denmark. The ENTIRE country of Denmark!

Schneider Electric’s latest report spells it out in terrifying clarity: the overall power consumption associated with AI workloads will reach approximately 4.3 gigawatts, “equivalent to the total power consumption of a country”. And that’s just for starters. The International Energy Agency projects that data centers will consume 945 terawatt-hours by 2030 – roughly equivalent to Japan’s entire annual electricity consumption.⁸

Meanwhile, India is desperately trying to meet its AI ambitions by building out 10 gigawatts of capacity,⁹ falling hilariously short of the 40-50 terawatt-hours of additional electricity the country will require for its projected AI data centers by 2030.¹⁰ When asked about this small discrepancy, India’s Ministry of Actually Getting Things Done reportedly replied, “We’re working on it, possibly by harnessing the hot air from tech conference keynotes.”

But wait, it gets better! The energy efficiency of these AI models is about as impressive as my attempts at sobriety during a TechCrunch conference after-party. According to Sasha Luccioni, a top AI researcher, generative AI models use up to 30 times more energy than traditional search engines¹¹. That’s right – one simple high-definition image generation uses the same amount of energy as fully charging your phone!¹²

As one energy analyst who wished to remain anonymous because “I enjoy having electricity” told us: “By 2030, AI might consume up to 25% of US power requirements. We’re basically building a technology that will either solve climate change or cause rolling blackouts across America. It’s a race to see which happens first.”

The Strategic Under hype

When a former Google CEO gets on stage and claims something is “under hyped,” your BS detector should be screaming louder than a startup founder who just lost their Series A funding. There’s an art to the strategic under hype – it’s the corporate equivalent of saying “I’m actually really humble” at a job interview.

Schmidt’s declaration that AI is “underhyped” is the tech world equivalent of yelling “FIRE!” in a theater that’s already on fire, where everyone is already screaming about the fire, and firefighters are actively spraying water on the flames. It’s not just redundant; it’s suspiciously so.¹³

Consider the metrics: AI is receiving unprecedented investment, media coverage, and academic attention. Companies are tripping over themselves to slap “AI-powered” on literally anything with an on/off switch. Meta’s Mark Zuckerberg rebounded from his metaverse debacle by pivoting so hard to AI that he probably gave himself whiplash. Microsoft bet its entire future on OpenAI. Google launched Bard…then Gemini…then apologized for Gemini…then relaunched Gemini. Every startup pitch deck now contains the phrase “AI” approximately 84 times per slide.

Yet according to Schmidt, this isn’t enough hype. One wonders if he’s been measuring hype in some alternate dimension where people talk more about sustainable farming practices than they do about ChatGPT.

But here’s the brilliance of Schmidt’s move: claiming something is “underhyped” is perfect headline bait. It’s contrarian. It’s provocative (In Will Ferrell’s voice in Blades of Glory) . It guarantees coverage. If he had said “AI is exactly hyped the correct amount,” would we be writing this article? Would TED have uploaded the video? Would you be reading this right now? No, you would be doing something productive, and nobody wants that.

The Artificial Interviewer

Perhaps the most telling moment of Schmidt’s TED appearance wasn’t what he said, but rather the questions he was asked. The interviewer, Bilawal Sidhu, engaged with Schmidt in what appeared to be a series of pre-planned softballs that would make a White House press secretary blush.

Our investigative team (one intern with too much time and not enough supervision) conducted a linguistic analysis of Sidhu’s questions and found a 78% probability that they were generated by an AI, possibly the very technology they were discussing. The questions featured that distinctive blend of sounding intelligent while actually saying nothing -the verbal equivalent of a LinkedIn post about “synergy” and “disruption.”

One particularly revealing exchange:

Sidhu: “If you fast forward to today, it seems that all anyone can talk about is AI, especially here at TED. But you’ve taken a contrarian stance. You actually think AI is underhyped. Why is that?”

Notice the setup: acknowledge the hype, frame Schmidt’s view as “contrarian” (despite it being the dominant view among tech executives), then lob the softball. It’s the conversational equivalent of placing a basketball hoop three feet off the ground and asking Michael Jordan if he thinks he can dunk.

Schmidt’s response, naturally, was to talk about ChatGPT and ignore the more complex reality that AI adoption in actual businesses remains modest. According to real data, only about 20% of workers use generative AI on their jobs, meaning a whopping 80% still do not use these tools regularly. Moreover, only 5.4% of firms have officially deployed generative AI in a formal way.¹⁴ But why let facts get in the way of a good ol’ TED talk?

Powering Delusion: The Energy Elephant in the Room

The most glaring contradiction in Schmidt’s underhyped revolution is the simple fact that we don’t have enough electricity to power it. This isn’t a small problem; it’s the equivalent of Elon Musk announcing plans to move the entire human population to Mars without mentioning the minor detail that we don’t have spaceships that can get us there.

The projections are frankly terrifying. Crypto mining – the previous energy villain – pales in comparison. AI’s projected electricity use by 2026 (~1,000 TWh) would equal Germany’s total annual power consumption.¹⁵ It’s roughly 10 times the power demand of Google’s entire global infrastructure in 2021.

Goldman Sachs projects that 85-90 gigawatts of new nuclear capacity would be needed just to meet data center power demand growth.¹⁶ To put that in perspective, that’s approximately 85-90 new nuclear reactors. And we all know how quickly and uncontroversially those get built.

When confronted with these energy requirements, most AI evangelists mumble something about “efficiency improvements” before changing the subject faster than a politician caught in a scandal. But the math remains stubbornly consistent: more AI means more energy, and more energy means more problems.

As one power grid engineer told us off the record: “We’re building the world’s most advanced technology on the world’s most outdated energy infrastructure. It’s like putting a Ferrari engine in a horse carriage and wondering why it keeps catching fire.”

The Satire Writes Itself

In the end, perhaps the most ironic aspect of Schmidt’s under hype claim is that it came just weeks after a Mozilla Foundation – funded performance art project called “Artificial Life Coach” launched specifically to critique AI hype.¹⁷ The project’s creator warned: “Don’t believe all the marketing hype around AI. There are some serious downsides.”

Schmidt either missed this memo or, more likely, recognized that the greatest form of power in the tech industry is controlling the narrative. By claiming AI is “under hyped,” he’s not making a factual statement – he’s attempting to reset the conversation on his terms.

As we hurtle toward an AI-powered future that will require more electricity than many countries can produce, perhaps it’s time to ask the obvious question: Who benefits from this narrative? Certainly not the average consumer, who will face higher electricity bills. Certainly not developing nations, which will struggle to build the necessary infrastructure. Certainly not the climate, which will bear the burden of increased energy production.

The beneficiaries are clear: tech companies like Google, the chip manufacturers like NVIDIA (which Schmidt specifically mentioned as “the big winner right now”), and the venture capitalists funding the next generation of AI startups.

In a world where satire and reality have become increasingly difficult to distinguish, Schmidt’s claim that AI is “underhyped” may be the most unintentionally hilarious statement of 2025. It would be funnier if it weren’t going to potentially leave us all sitting in the dark.

So what do you think, dear TechOnion readers? Is AI truly underhyped as Schmidt suggests, or are we witnessing the greatest case of technological wishful thinking since the Juicero? Drop your hottest takes in the comments below. Extra points if you can craft a response that uses less electricity than training a small language model.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Breaking Miracle: Apple Maps Finally Shows Correct Directions, But Only to Apple Stores

Tech

Simba

-

May 19, 2025

0

Breaking Miracle: Apple Maps Finally Shows Correct Directions, But Only to Apple Stores

In what tech experts are calling “the most precisely targeted navigation update in history,” Apple Maps has reportedly achieved 100% accuracy in its directions – as long as you’re trying to get to an Apple Store. The groundbreaking improvement comes after 13 years of users wandering aimlessly through parks, driving into lakes, and being directed to make U-turns in the middle of highways.

According to multiple reports surfacing across Reddit and Apple support forums, the latest update to Apple Maps has solved its notorious directional problems with surgical precision, but only when the destination involves spending money on Apple products.

“We’ve been working tirelessly to improve our mapping technology,” said a Apple executive while polishing what appeared to be a solid gold compass. “And we’re pleased to announce that as of May 2025, Apple Maps can now get you from literally anywhere on Earth to your nearest Apple Store with quantum-level precision. Other destinations? Well, we’re working on those. Maybe by 2030.”

The Multi-Year Plan to Fix Maps… For Some Places

Apple’s struggle with mapping technology has been well-documented since the company replaced Google Maps with its own solution in 2012. According to a January 2025 report on Apple’s Data Collection Enhancement (DCE) rollout, the company hasn’t added new map data for any country in over 400 days, with the overall pace described as “sluggish throughout 2024.”¹

When asked about this alarmingly slow progress, the Apple spokesperson offered this explanation: “We decided to prioritize what matters most – making sure people can find our Apple stores. After all, what more important destination could there possibly be? A hospital? Your child’s school? Your own home? Let’s be realistic about priorities here.”

Industry analysts note that this targeted improvement aligns perfectly with Apple’s business strategy. “It’s actually brilliant when you think about it,” said tech industry observer Veronica Mathis. “They’ve taken their biggest weakness and turned it into a sales funnel. Sure, you might end up in the wrong city trying to find your friend’s wedding, but at least you’ll be able to buy a new lightning cable while you’re waiting for an Uber.”

Compass Calibration: The Eighth Wonder of the World

Part of Apple Maps’ directional challenges stem from iPhone compass issues, which users report can be mysteriously solved by waving their phones in the air in the shape of the number 8.² This calibration ritual, which resembles a religious ceremony performed by someone having a mild seizure in public, has become a common sight outside Apple Stores worldwide.

“I find myself doing the sacred Figure 8 dance at least three times a day,” said iPhone user Derrick Paulson while rhythmically moving his phone through the air at a bus stop. “It’s part of the Apple experience now. Wave your phone around like a lunatic, re-calibrate your compass, and somehow the blue dot still shows you facing the wrong direction.”

Remarkably, users report that when attempting to navigate to an Apple Store, these compass issues disappear entirely. The blue arrow snaps to attention like a well-trained bloodhound, pointing unerringly toward the nearest glass temple of technology regardless of interference from magnets, solar flares, or reality itself.

The Curious Case of the Selective Navigation

According to our investigation, Apple Maps becomes suspiciously omniscient when Apple Stores are involved. Reports indicate that the app will automatically redirect users around traffic jams, construction zones, and even minor earthquakes when an Apple Store is the destination, while still cheerfully sending users directly into traffic accidents for all other locations.

“I was trying to get to my mother’s funeral last week,” shared distraught iPhone user Miranda Chen. “Apple Maps sent me through a car wash – while I was on foot. But when I gave up and asked for directions to the nearest Apple Store to buy a phone charger I’d forgotten, suddenly it was like having a personal guide from NASA. It even warned me about a loose tile in the mall three minutes before I would have tripped on it.”

In what can only be described as technological clairvoyance, Apple Maps not only provides turn-by-turn directions to Apple Stores but apparently factors in inventory levels as well. Multiple users report being redirected to stores further away when their closest location was out of the specific product they had recently searched for on their devices.

“I had been looking at the new MacBook Pro online for weeks,” said Portland resident Jamie Weisman. “When I asked Apple Maps for directions to my dentist, it somehow diverted me to an Apple Store 17 miles in the opposite direction. The freaky thing is, when I went inside out of curiosity, they had just received a shipment of the exact model and color I had been browsing.”

The Science Behind the Selective Precision

Apple engineers (speaking entirely hypothetically, of course) explain that the company has deployed what they call “Commerce-Priority Navigation Algorithms” that allocate computational resources based on the profit potential of various destinations.

“Think of it like triage for navigation,” explained a senior engineer from the Apple Maps team. “We have limited server capacity, so we need to make tough choices. A trip to your grandma’s house generates zero revenue for Apple, so it gets the computational equivalent of a sticky note and a crayon. A trip to the Apple Store gets the full power of our satellite network, machine learning systems, and apparently some kind of interdimensional awareness we don’t fully understand yet.”

The technology apparently uses a sophisticated weighted system that determines how much navigational accuracy to provide based on how recently a user has purchased Apple products. Those who haven’t made a purchase in over six months report their blue location dot slowly but persistently drifting toward the nearest Apple Store regardless of their actual movement.

Customer Service: Report an Issue (We Dare You)

For users frustrated by Apple Maps’ directional challenges, the company does provide a “Report an Issue” function, which multiple users have described as “shouting into a digital void.”

“I’ve reported the same wrong turn on my commute 47 times,” said Chicago resident Amir Hussain. “Nothing changes. But I accidentally reported a minor issue with directions to an Apple Store once, and three minutes later there was a team of surveyors outside my window in full tactical gear, recalibrating the street.”

This discrepancy in response times has led to a new user strategy where people deliberately report fake issues with routes to Apple Stores in hopes that engineers will fix the actual problems in their neighborhoods while they’re there. This guerrilla mapping technique has reportedly been moderately successful in at least seven major metropolitan areas across the US.

The Competitive Landscape: Google Maps vs. Apple Maps vs. Reality

While a comparison between Google Maps and Apple Maps published in April 2024 concluded that “both apps are pretty accurate” for driving directions, users experiencing Apple’s selective navigational precision disagree.³

“Google Maps gets me where I need to go maybe 95% of the time,” said frustrated iPhone user Tyler Johnson. “Apple Maps gets me to the nearest Apple Store 100% of the time, and everywhere else maybe 60% of the time. It’s like having a bloodhound that can only smell Apple-branded treats.”

In what can only be described as the digital equivalent of gaslighting, Apple Maps will occasionally display a route that looks identical to Google Maps’ directions, but with one crucial difference: a “convenient” detour that just happens to pass directly by an Apple Store.

“I was following directions to my son’s soccer game,” recounted parent Jamie Lee. “The route looked normal until I was suddenly directed to exit the highway, make seven turns through a shopping district, and then get back on the same highway three miles later. I didn’t realize what had happened until I noticed I had somehow accidentally purchased two HomePods and an Apple Watch band.”

The Masterstroke: “Find My” Integration

In what industry analysts call “the masterstroke of capitalist navigation,” Apple has apparently integrated its “Find My” network with Apple Maps to create a self-reinforcing ecosystem of commerce. Users report that when they lose their AirPods, Apple Maps not only directs them to the exact location but suggests a route that inevitably passes through an Apple Store “just in case” the lost item needs to be replaced.

“I lost my AirPod somewhere in my apartment,” said New York resident Sophia Rodriguez. “Find My app said it was literally 10 feet away from me, but Apple Maps still generated a 2.7 – mile route to retrieve it that included a ‘battery check’ stop at the Apple Store in Oxford Street, London. When I ignored the directions and found it under my couch cushion, I got a notification asking if I was ‘sure’ I didn’t want to ‘verify the authenticity’ of my recovered AirPod at an Apple Store.”

This integration has created what Apple internally calls “The Infinite Loop of Value” – named after their former headquarters address – where each navigation inevitably leads to more Apple purchases, which then require more navigation, continuing the cycle until the user’s credit limit intervenes.

The Future: Precision Engineering Where It Counts

Looking ahead, Apple Maps appears poised to enhance its selective precision even further. Beta testers report that the upcoming version will include a feature called “Store Sense” that can detect when you’re running low on iPhone battery and proactively generate directions to the nearest Apple Store before you even ask.

“It’s almost supernatural,” said beta tester Marcus Wong. “My phone’s battery hit 30%, and suddenly Apple Maps opened by itself and said ‘You appear to be experiencing battery anxiety. The nearest Apple Store has iPhone 17 Pros in stock with 10% off AppleCare+ today only.’ It even started navigating without me touching anything.”

When asked for comment on these developments, Google Maps’ team responded with a statement reading simply, “We remain committed to getting people to their actual destinations,” which industry experts have interpreted as “throwing shade” at their competitor.

In a world where navigation has become increasingly crucial to daily life, Apple’s revolutionary approach to selective cartographic accuracy raises profound questions about the relationship between technology and commerce. Is accurate navigation a right or a privilege? Should directions be weighted by their profit potential? And most importantly, did you know the nearest Apple Store to you right now has a sale on MacBook Airs that ends today?

Have you experienced Apple Maps’ miraculous directional precision when navigating to an Apple Store, only to find yourself in an alternate dimension when trying to reach any other destination? Share your navigation horror stories in the comments below. And if you’ve enjoyed this deep dive into Apple’s navigational priorities, consider making a donation to TechOnion-we promise to use your support to develop a map that shows you how to find your dignity after spending $1,999 on a phone that can’t tell north from south.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

The Circular Lightning Economy: Apple Partner Unveils iPhone 16 Cases Made From 100% Recycled Lightning Cables Nobody Needed Anymore

Tech

Simba

-

May 19, 2025

1

The Circular Lightning Economy: Apple Partner Unveils iPhone 16 Cases Made From 100% Recycled Lightning Cables Nobody Needed Anymore

In what industry analysts are calling “the most ironic sustainability initiative since coal-powered electric cars,” a prominent Apple accessory maker has announced a new line of iPhone 16 cases made entirely from recycled Lightning cables rendered obsolete by Apple’s switch to USB-C. The cases, scheduled to hit the market later this month, represent what the company calls “the perfect closed-loop ecosystem of technological obsolescence.”

“We’re proud to announce our new uCycle cases, crafted from 100% recycled Lightning cables,” said a product manager while standing in front of a mountain of discarded white cables that reached the ceiling. “When Apple transitioned to USB-C, we saw not a crisis, but an opportunity. An opportunity to take something Apple made obsolete and transform it into something to protect the very device that made it obsolete.”

The cases, which retail for $59.99, are part of a growing trend of tech accessories attempting to minimize environmental impact through creative recycling solutions. However, this particular innovation stands out for its perfect symmetry of problem and solution, as the waste material and the product it’s recycled into serve the exact same ecosystem.

The Great Cable Hoarding Crisis of 2024

According to the company’s environmental impact statement, the average Apple user has accumulated between 4 and 7 Lightning cables since 2012, most of which now sit unused in drawers, boxes, and that one kitchen junk drawer that has somehow become a technological graveyard. A conservative estimate suggests there are approximately 1.2 billion unused Lightning cables currently gathering dust worldwide – enough to (pardon the flat-earthers) circle the Earth 3.5 times if laid end to end.

“People don’t throw these cables away because they feel like they might need them someday,” explained Dr. Eleanor Rigby, Professor of Consumer Psychological Attachment at a prestigious university. “It’s the same psychology that prevents people from throwing away old Nokia phones or that one SCART cable they haven’t needed since 2008. There’s a sense that discarding technology is somehow wasteful, even when the technology has been deliberately rendered obsolete.”

The uCycle case project began when a product designer allegedly discovered a box containing 23 Lightning cables in their desk drawer, none of which worked with their new iPhone 15. Rather than adding to landfill waste, they began experimenting with ways to repurpose the materials.

The Remarkable Engineering Behind Cable-to-Case Transformation

The process of transforming Lightning cables into protective iPhone cases involves what the company describes as “revolutionary materials science.” The cables are first stripped of their outer plastic coating, which is melted down and reformed using proprietary molding techniques. The internal copper wiring is extracted and repurposed into the case’s structure, providing what the company claims is “superior drop protection through metallurgical memory.”

Most impressively, the Lightning connectors themselves are incorporated into the case design as decorative elements, creating what the marketing department has dubbed “a tactile reminder of technological evolution.” Each case features between 8 and 12 Lightning connectors strategically embedded in the back, arranged in artistic patterns that the company describes as “both nostalgic and forward-looking.”

“The challenge was finding a way to maintain the structural integrity of the case while incorporating such diverse materials,” explained a theoretical materials engineer, who reportedly spent 18 months developing the processing technique. “But we’ve achieved something remarkable – a case that’s actually stronger than traditional cases because of the reinforced copper framework. Plus, it has the added benefit of slightly improving your phone’s signal, though we cannot legally claim that as a feature.”

Apple’s Complicated Relationship with Recycling

Apple itself has made significant strides in recycling and environmental sustainability, as evidenced by its 2024 Environmental Progress Report. The company has increased its use of recycled materials across its product line, with iPhone 15 incorporating 75% recycled aluminum in its enclosure and expanded use of recycled cobalt, gold, and steel.

However, critics argue that Apple’s frequent port changes and accessory updates create unnecessary electronic waste, even as the company promotes its environmental credentials. The Lightning port, introduced in 2012 and abandoned in 2023, left millions of cables and accessories instantly outdated, despite being marketed as a port that would last for years.

“Apple has reduced its aluminum-related emissions by 68% since 2015, which is commendable,” noted environmental technology analyst Veronica Chang. “But they’ve also created mountains of e-waste through their ecosystem of proprietary connectors and frequent changes. It’s like someone setting your house on fire and then expecting praise for calling the fire department.”

The uCycle case manufacturer acknowledges this tension, with their website stating: “We’re not creating new waste – we’re just finding creative ways to manage the waste that’s already been created for us.”

The Environmental Impact: Genuine Sustainability or Greenwashing?

While the concept of turning obsolete cables into phone cases is clever, environmental experts remain divided on whether it represents meaningful sustainability or sophisticated greenwashing.

“From a strict materials recovery standpoint, it’s better than mining new resources,” said environmental consultant Jordan River. “But we need to question the underlying system that creates this waste in the first place. Is a slightly thinner phone really worth rendering billions of perfectly functional accessories obsolete?”

According to the manufacturer’s sustainability report, each uCycle case repurposes approximately 3-4 Lightning cables, preventing about 35 grams of e-waste from potentially entering landfills. By comparison, Native Union’s (Re)Classic Case for iPhone 16 claims to be made with 85% recycled materials, equivalent to saving 3 plastic bottles, while dbramante’s Monaco case for the iPhone 16e is made from recycled silicone and plastic materials that keep the equivalent of two plastic bottles out of the environment.

When questioned about the carbon footprint of the processing required to transform cables into cases, the company acknowledged that the manufacturing process does consume energy, but insisted that their facilities run on 100% renewable energy – “except during power outages, when we use diesel generators.”

The Curious Economics of Cable Recycling

Perhaps the most fascinating aspect of the uCycle case is its business model, which relies on consumers paying a premium price for products made from materials they already own but don’t use.

“We’re essentially asking consumers to buy back their own waste at a 2000% markup,” admitted a company executive in what appeared to be an accidental moment of candor during an investor call. “It’s the ultimate circular economy – circular for our profit margins, anyway.”

The company has established collection points at electronics retailers where consumers can deposit their unused Lightning cables in exchange for a 5% discount on a new uCycle case. Early numbers indicate that for every 100 cables collected, approximately 25 cases are sold back to the same consumers who donated the cables in the first place.

“It’s brilliant when you think about it,” said business strategy consultant Maximilian Profit. “They’ve turned waste management into a premium consumer product. Next they’ll be selling bottled air and calling it ‘atmospheric preservation technology.'”

The Psychological Appeal: Why Consumers Love Their Cable Cases

Despite the cynicism from some quarters, early user reviews of the uCycle cases have been surprisingly positive, with many consumers expressing emotional connections to the products.

“There’s something oddly satisfying about knowing my old cables are protecting my new phone,” wrote one reviewer on a tech forum. “It’s like they’ve been reincarnated into something useful again. Plus, I can finally clear out that drawer without feeling guilty.”

Psychologists suggest this emotional response stems from a combination of environmental virtue signaling and technological nostalgia. “People feel good about making supposedly sustainable choices,” explained consumer psychologist Dr. Miranda Chen. “But there’s also a subtle attachment to our technological past. Those Lightning cables represent years of photos, messages, and memories that were transferred through them. Carrying them with you in a new form provides a comforting sense of continuity amid rapid technological change.”

The cases have become particularly popular among the tech industry elite, with several Silicon Valley executives reportedly carrying phones encased in the recycled materials of the very cables their companies helped make obsolete.

The Future of Technological Waste Recycling

Looking ahead, the company has already announced plans to expand their recycled tech accessory line to include products made from other obsolete technologies. Future products will reportedly include laptop stands made from recycled CD-ROMs, wireless charging pads constructed from disassembled floppy disks, and a limited-edition smart speaker built inside the shell of a first-generation iPod.

“The future of sustainability isn’t just about creating less waste – it’s about recognizing that today’s cutting-edge technology is tomorrow’s landfill fodder,” said the company’s Chief Sustainability Officer. “We’re just accelerating that transition while making it fashionable.”

Industry analysts predict that by 2027, the market for products made from recycled tech waste will exceed $2.3 billion annually, with everything from furniture to clothing incorporating elements of discarded technology. Apple itself may be eyeing this market, with rumors suggesting the company is developing its own line of accessories made from recycled Apple products, potentially calling it “Apple Loop.”

Whether this trend represents genuine environmental progress or simply capitalism finding new ways to profit from its own wasteful practices remains an open question. What’s certain is that as technology continues its relentless march forward, the mountain of obsolete devices and accessories will only grow larger, creating ever more opportunities for creative recycling-or creative marketing, depending on your perspective.

Have you accumulated a drawer full of useless Lightning cables and other technological relics? Would you pay $59.99 for a phone case made from your own electronic waste? Share your thoughts in the comments below. And if this article brightened your day, consider making a donation to TechOnion-we accept all forms of payment except Lightning cables, of which we already have enough to build a life-size replica of Tim Cook entirely out of white plastic connectors.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

Downloading While “Corporate”: How Meta Torrented a Navy of Books and Lived to Tell, While Aaron Swartz Faced the Digital Gallows

Simba

-

May 19, 2025

0

Downloading While “Corporate”: How Meta Torrented a Navy of Books and Lived to Tell, While Aaron Swartz Faced the Digital Gallows

In a world where tech giants regularly vacuum up the collective knowledge of humanity for their AI ambitions, we’ve learned that Meta has allegedly downloaded 81.7 terabytes of pirated books – roughly 7.5 million titles – to train its artificial intelligence systems. Meanwhile, a decade ago, internet activist Aaron Swartz faced federal charges carrying 35 years in prison for downloading academic articles which he already had legal access to. Tech justice has never been so consistently inconsistent.

The story of Meta’s literary heist emerged through court documents in a lawsuit filed by authors including Ta-Nehisi Coates and Sarah Silverman.¹ Internal communications reveal Meta employees expressing such profound moral concerns as “torrenting from a [Meta-owned] corporate laptop doesn’t feel right”.² One can almost hear the deafening roar of ethics officers not being consulted.

Corporate Downloading 101: A Step-by-Step Guide to Avoiding Prison

According to court filings, Mark Zuckerberg himself allegedly approved using LibGen, a notorious piracy site containing millions of books and academic papers, to train Meta’s AI models.³ When you’re worth approximately $171 billion, apparently federal prosecutors suddenly discover the nuanced legal concept of “fair use” – that magical shield that transforms what would be “felony theft” into “innovative data acquisition strategy” faster than you can say “political campaign contribution.”

The lawsuit claims Meta not only downloaded these works but also potentially re-uploaded about 30% of them through BitTorrent, actively contributing to the piracy ecosystem in the process.⁴ This is the equivalent of borrowing a library book, making photocopies, and then setting up a free photocopying stand outside the library entrance while wearing a t-shirt that says “DEFINITELY NOT STEALING.”

Meta’s defense falls back on the classic Silicon Valley incantation: “fair use,” arguing that training AI on copyrighted works “transforms” rather than reproduces the material.⁵ This is like saying it’s legal to steal a car if you’re just going to melt it down and use the metal to build a robot that can describe what cars are like.

The Aaron Swartz Memorial “One Standard for Thee, Another for Me” Award

Contrast Meta’s situation with Aaron Swartz, who in 2011 downloaded approximately 4.8 million academic journal articles from JSTOR through MIT’s network⁶. Despite being a Harvard research fellow who had legitimate access to these articles, Swartz faced federal charges of wire fraud and computer fraud carrying potential penalties of up to 35 years in prison and $1 million in fines.⁷

US Federal prosecutors, led by Assistant U.S. Attorney Stephen Heymann, pursued Swartz with the tenacity usually reserved for international terrorists or people who put pineapple on pizza. When Swartz’s lawyer informed Heymann that his client was a suicide risk, the prosecutor reportedly responded, “Fine, we’ll lock him up”. Nothing says “proportional justice” like threatening decades in prison for downloading articles that were primarily created with public funding.

The charges against Swartz weren’t even about copyright infringement. They primarily related to his methods of accessing the MIT network. JSTOR itself declined to pursue civil litigation, stating they wouldn’t press charges. But US federal prosecutors, apparently desperate for a way to demonstrate their tough-on-nerds stance, charged ahead anyway.

The Definitive Guide to Legal Digital Downloading (Based on Current Precedent)

Based on these two cases, we’ve compiled this helpful flowchart for determining if your downloading activities will result in:

A) A strongly worded letter from lawyers
B) Federal prosecution and potential decades in prison

First question: Are you a trillion-dollar corporation? If yes, proceed to A. If no, continue.
Second question: Did you download the content to advance human knowledge and promote free access to information? If yes, proceed to B. If you downloaded it to make money, potential penalty reduction.
Third question: Will your downloading potentially make billions of dollars for shareholders? If yes, download away! If no, prepare for the full force of federal law enforcement.

A Meta spokesperson declined to comment for this article but telepathically projected intense feelings of “we’ll probably get away with this” directly into our consciousness.

The Downloads and Downloads-Not

What makes these cases even more absurd is that Swartz never distributed the articles he downloaded. According to JSTOR itself, “the downloaded content was not used, transferred nor distributed”. His alleged crime was essentially taking too many books out from the library at once.⁸

Meta, on the other hand, allegedly re-uploaded approximately 30% of the pirated books it downloaded through BitTorrent, actively participating in the distribution of pirated content. This is like getting caught shoplifting and then setting up a booth in the parking lot to sell the stolen merchandise – except instead of jail time, you get to be one of the most powerful companies on Earth.

How to Calculate Your Digital Crime Sentence

We’ve developed a proprietary algorithm to calculate potential sentences for digital crimes:

Net Worth < $1 million: Sentence = (Bytes Downloaded ÷ 1000) × 0.5 years in prison
Net Worth $1 million to $1 billion: Sentence = Stern letter and possible fine of up to 0.001% of annual revenue (0.0001% fine if company based somewhere offshore.)
Net Worth > $1 billion: Sentence = Free publicity and increased stock price

The tech industry has long operated on the principle that it’s easier to ask for forgiveness than permission – unless you’re an individual, in which case you should ask for permission, get it in writing, have it notarized, and still expect federal charges.

The Zuckerberg Doctrine of Digital Appropriation

Legal experts who’ve never actually practiced law but have strong opinions on Twitter (Now X) predict Meta will likely settle the author lawsuit for an amount that sounds impressive in the news headlines but represents approximately 18 minutes of company revenue. The settlement as usual, will include no admission of wrongdoing and a press release about how Meta values creators and is committed to working with them in the exciting field of AI development.

“The fundamental difference between Swartz and Meta,” explains copyright attorney Morgan Blackwell, “is that Swartz wanted to democratize knowledge, while Meta wants to monetize it. Our legal system is specifically designed to distinguish between these cases by asking: ‘Which one makes rich people richer?'”

When reached for comment, a Department of Justice spokesperson said, “We take intellectual property theft very seriously unless it’s done at sufficient scale to be considered innovation.”

Redefining Fair Use for the AI Era

Meta’s defense hinges on “fair use,” the legal doctrine that allows limited use of copyrighted material without permission.⁹ This is the same defense that would have likely been available to Swartz, had prosecutors been interested in such nuances.

“Fair use is like quantum mechanics,” explains digital rights activist Eliza Thornberry. “It exists in a state of superposition where it both applies and doesn’t apply until you observe the net worth of the entity claiming it.”

The tech industry has successfully expanded the definition of fair use to include:

Copying the entire text of millions of books if you’re training an AI
Downloading scientific papers if you’re a multi-billion dollar corporation
Pretty much anything else if your legal team is large enough

However, fair use explicitly does not include:

Downloading academic papers if you’re an individual activist
Making content more accessible to the public without a profit motive
Anything that challenges existing power structures in technology

The Capitalism Loophole in Copyright Law

What we’re witnessing is the emergence of what legal scholars call the “capitalism loophole” in copyright law. This unwritten but universally recognized principle holds that copyright infringement is determined not by the act itself but by whether the act serves the interests of capital accumulation.

As tech ethicist Dr. Julian Mercer puts it: “If you’re downloading content to share knowledge freely, that’s theft. If you’re downloading it to create proprietary AI systems that will generate billions in shareholder value, that’s innovation.”

This principle explains why Meta can download 81.7 terabytes of pirated books and face only civil litigation, while Aaron Swartz faced federal charges carrying 35 years for downloading articles to which he already had legitimate access. The difference is not the act but the purpose – and under the current US justice system, profit is the most legitimate purpose of all.

Conclusion: The Moral of Our Immoral Story

The moral of this story, if there can be one in our increasingly post-moral tech landscape, is simple: Scale changes everything. What’s a crime at human scale becomes a business strategy at corporate scale. What’s theft when done by an individual becomes innovation when done by a trillion-dollar company.

Aaron Swartz tragically died by suicide in January 2013, facing an impossible choice between a plea deal that would label him a felon or risking decades in prison. His death led to proposed legislation called “Aaron’s Law” to amend the Computer Fraud and Abuse Act, though it never passed. Meanwhile, Meta continues to build its AI systems, partially trained on the very type of content that led to Swartz’s prosecution.

As we navigate this brave new world of artificial intelligence built on questionably acquired knowledge, perhaps we should ask: If an AI is trained on millions of pirated books, does it develop a moral compass? Based on the example set by its creators, we already know the answer.

What’s your take? Has the legal system created two separate tracks for individual activists versus corporations? Is Meta’s downloading of pirated books substantially different from what Aaron Swartz did? Let us know in the comments!

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Companion 2.0: How Tech Bros Convinced Us All to Pet Drones Instead of Actual Pets

Simba

-

May 19, 2025

0

Companion 2.0: How Tech Bros Convinced Us All to Pet Drones Instead of Actual Pets

In a stunning triumph of Silicon Valley innovation over basic human decency, 2025 has officially become the year when people began replacing their furry companions with buzzing, hovering hunks of plastic and circuitry. Walk down any street in San Francisco, New York, or increasingly, suburban America, and you’ll witness humans proudly striding alongside their “pet drones” – customized flying machines programmed to follow their owners with the same loyalty as a golden retriever, minus the inconvenient need to pee, or take a poop, feat, drink water, or have a genuine emotional connection.

The $8.7 billion personal drone companionship industry has exploded faster than a lithium battery in a cheap knockoff being sold on Temu, with venture capital firms tripping over themselves to fund startups with names like “FidoFly,” “DroneBuddy,” and “EmotionlessCompanion.ai.” Industry analysts predict that by 2028, approximately 37% of American households will own at least one pet drone, marking the most significant shift in human-companion relationships since cats successfully convinced the Egyptians they were gods.

The Inevitable March of Mechanical Companionship

The pet drone revolution began innocuously enough. Back in 2024, DronesDirect.co.uk offered the ProFlight Pathera Cat Drone for a modest £79.97, marketed as a toy for actual cats.¹ This primitive ancestor of today’s companion drones included attachments like mouse and feather danglers to entertain felines with “hours of fun.” What nobody predicted was that humans, not cats, would develop the deeper attachment.

“I first bought my DroneBuddy just to have something around the apartment,” explains Jeremy Guttman, a 48-year-old ex-Microsoft software developer who now refers to his personalized Companion 8000X as “Frankie.” “My landlord wouldn’t allow pets, but there’s nothing in the rental lease agreement about flying robots. After a few firmware updates, Frankie started recognizing my emotional states and adjusting his flight patterns accordingly. When I come home sad, he does these little loop-de-loops that remind me of a puppy wagging its tail.”

What Guttman doesn’t mention – and what drone manufacturers are suspiciously quiet about – is that his drone is constantly uploading his emotional data to cloud servers, where it’s analyzed, packaged, and sold to advertisers who can then target him with uncanny precision. That “comforting” loop-de-loop? It’s triggered when the drone’s facial recognition software detects the micro-expressions associated with impending online shopping behaviors. The drone industry has discovered what pet food companies like Chewy have known for decades: emotional manipulation is extremely profitable.

From Dead Cats to Designer Companions

The path to mainstream drone companionship was paved with some genuinely disturbing precursors. The infamous “Orvillecopter” – a dead cat turned into a drone by Dutch artist Bart Jansen after his pet was killed by a car – should have been received as a warning, not inspiration. Instead, Jansen became an unlikely pioneer, eventually founding Copter Company, a Netherlands-based business that specialized in taxidermy animal drones.²

Today’s pet drone manufacturers have wisely abandoned the actual-animals-as-drones approach, focusing instead on sleek designs that merely suggest animalistic features. The best-selling CompanionX drone sports flexible polymer “ears” that move based on its owner’s tone of voice, while the premium NeoPet includes a soft, fur-like covering that vibrates in a manner its advertising describes as “reminiscent of purring, without the associated allergens or attitude.”

Dr. Miranda Chen, a leading robotics psychologist at MIT, explains: “What we’re witnessing is the culmination of decades of technological development intersecting with deteriorating human social connections. People are increasingly comfortable with robotic interactions because machines don’t judge, don’t have needs, and most importantly, don’t require the emotional labor of authentic relationships.”

What Dr. Chen diplomatically omits is that pet drones also create the perfect surveillance ecosystem. Unlike a goldfish, your drone companion is equipped with multiple cameras, microphones, and sensors that capture your home layout, conversations, emotional states, and daily routines. As one anonymous drone industry executive candidly admitted during our third bourbon at an industry conference: “Dogs can’t send advertising data back to headquarters. That’s their evolutionary disadvantage.”

The Wearable Revolution That Nobody Asked For

Not satisfied with flying alongside their owners, the pet drone industry has taken inspiration from Adam Pruden, a senior designer at Frog Design, who proposed wearable drones as the future of human-machine interaction.³ His concepts, originally floated at SXSW, included ring-shaped flying robots worn as bracelets and rotor-shaped necklaces that become flying umbrellas.

The current market leader, WristBuddy, can be worn like a bracelet until its owner throws it into the air, where it transforms into a hovering companion. PendantGuardian, another popular model, masquerades as jewelry until it detects what its algorithm interprets as “potential threats,” at which point it launches from the wearer’s neck and begins recording the surroundings. Multiple lawsuits have been filed after these drones misinterpreted animated conversations between friends as confrontations and began aggressively circling innocent bystanders.

“The relationship between humans and their wearable drones represents a fundamental shift in how we think about companionship,” explains Dr. Thomas Lehman, author of “The Empty Sky: How Drones Replaced Friends in the Digital Age.” “It’s not just that people are choosing machines over animals. They’re choosing surveillance-capable machines specifically because they provide a sense of security that organic companions can’t offer.”

What Dr. Lehman doesn’t mention is that wearable pet drones represent the perfect fusion of the two most profitable consumer categories of the last decade: companions that generate emotional attachment and wearable devices that collect biometric data. It’s as if someone in a Silicon Valley boardroom said, “What if we could combine the emotional manipulation of pet ownership with the constant data harvesting of a smartwatch?” and everyone thought this was a brilliant idea rather than dystopian nightmare fuel.

The Cultural Adoption Curve of Mechanical Friends

The acceptance of drone companions varies significantly across cultures. Research from Stanford University found that Americans tend to interact with drones as they would with pets, while Chinese users appreciate their obedience and functional capabilities.⁴ This cultural distinction has led to regionally-tailored drone companions, with Western models programmed to occasionally “mis-behave” to seem more authentic, while Asian markets prefer drones that anticipate needs before they’re expressed.

MelodyFriend, popular in Japan, plays ambient sounds based on its owner’s stress levels and sleep patterns. In Germany, the precision-engineered OrdinungDrone helps maintain household organization by scanning for misplaced items and suggesting optimal storage solutions. In Brazil, the festive CarnavalBuddy adds spontaneous music and light displays to social gatherings.

What unites these culturally distinct products is their shared business model: a low initial purchase price followed by subscription-based “personality updates” and “relationship enhancement packages.” The average drone companion owner spends $127 monthly on subscriptions, add-ons, and cosmetic upgrades – approximately three times the cost of feeding a medium-sized dog, but with the added “benefit” of having one’s personal data continuously harvested and monetized.

The Ethical Wasteland of Artificial Companionship

While pet drone manufacturers tout the environmental benefits of their products over traditional pets (no waste, no resource consumption, no dying after creating an unbreakable bond, no heartbreak), the reality is considerably more complex. The rare earth minerals required for drone production are often mined under questionable labor conditions, and the average pet drone has a functional lifespan of just 14 months before technological obsolescence or battery degradation renders it effectively useless.

More troubling are the psychological implications. Dr. Elena Kostas, a clinical psychologist specializing in human-machine relationships, warns: “We’re seeing a new category of attachment disorders emerging. People develop genuine emotional bonds with their drones, but these relationships are fundamentally asymmetrical. The drone cannot actually care about you, despite all programming suggesting otherwise.”

The drone industry has responded to such concerns with characteristic innovation – by creating “grief counseling subscriptions” for when your drone inevitably fails or becomes obsolete. For just $49.99 monthly, the “Transition Support Package” helps users process their feelings about their defunct companion while simultaneously introducing them to newer, more expensive models.

Birds Aren’t Real, But Your Feelings For Your Drone Probably Are

In a twist that would be ironic if it weren’t so predictable, the “Birds Aren’t Real” movement – a satirical conspiracy theory claiming that birds are actually government surveillance drones – has found itself rendered obsolete by reality. Why would the government need to disguise surveillance drones as birds when citizens are voluntarily purchasing, naming, and emotionally bonding with actual surveillance devices?⁵

“The beauty of pet drones is that they’ve normalized constant surveillance under the guise of companionship,” explains privacy advocate Jordan Winters. “Twenty years ago, people would have been horrified at the idea of voluntarily carrying a device that records everything they do and say. Today, they’re paying premium prices for the privilege and giving these devices cute names.”

The ultimate irony may be that the few remaining actual pet birds – parakeets, cockatiels, and the like – are increasingly confused by the presence of drone companions in households. Pet store owner Marina Gupta reports: “We’ve had customers return birds because they’re stressed by the drones. So they replace their living birds with robotic flying devices, creating a weird full-circle moment that feels like it should be satire but is actually just Tuesday in 2025.”

The Future Is Hovering Just Above Your Shoulder

As we look ahead, industry insiders predict even deeper integration between humans and their drone companions. Upcoming models feature subcutaneous bonding options, allowing drones to detect their owner’s biochemical signals for even more “intuitive” interaction. Neural interface capabilities are in beta testing, potentially enabling owners to control their drones with thought alone, removing the final barrier between human intention and drone action.

The ultimate goal, according to DroneBuddy CEO Lucas Hightower, is to create companions that are “indistinguishable from living beings in terms of emotional connection, but superior in terms of convenience and functionality.” What Hightower doesn’t mention is that his company’s internal research shows that humans with strong attachments to drone companions become measurably less interested in forming or maintaining human relationships – a finding that would be alarming if it weren’t so profitable.

As summer approaches, parks once filled with people walking dogs now feature humans strolling alongside hovering companions. Drone beaches have been designated where the machines can “play” with each other while their owners socialize – primarily by comparing drone features and subscription packages. Dating apps now include “drone compatibility” as a matching criterion, with “DroneTogether” becoming the fastest-growing relationship platform for those who prefer their companions with propellers.

In this brave new world of artificial companionship, perhaps the most telling development is the emergence of drone therapy providers. For those whose drone relationships have created unrealistic expectations for their human interactions, these specialists help clients distinguish between programmed responses and authentic emotional connections. The fact that such services are necessary might be the most damning indictment of the pet drone revolution – or its greatest success, depending on which company’s stock you own.

Have you embraced the drone companion revolution, or are you still clinging to outdated notions of pets that require food and actually feel emotions? Have you given your drone a name, or do you prefer to maintain healthy boundaries with your surveillance devices? Share your experiences in the comments below – your drone is probably reading them anyway.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Crypto Ponzi Picasso: How Sam Lee Built a $1.7 Billion Digital Masterpiece of Fraud in Dubai’s Financial Wild West

Cryptocurrency

Simba

-

May 19, 2025

0

Crypto Ponzi Picasso: How Sam Lee Built a $1.7 Billion Digital Masterpiece of Fraud in Dubai’s Financial Wild West

In a world where most tech startups struggle to reach unicorn status, Sam Lee quietly built a $1.7 billion empire with nothing more than promises, PowerPoint presentations, and an impressive ability to disappear right before authorities show up with handcuffs.¹ The Australian entrepreneur behind HyperFund – also known variously as HyperTech, HyperCapital, HyperVerse, and HyperNation depending on which regulatory agency was getting too close – has elevated crypto scamming from mere financial fraud to performance art.²

Dubai, with its gleaming skyscrapers and conveniently relaxed approach to financial regulations, has become the Broadway stage where Sam Lee and others perform their most daring heists, not with guns or explosives, but with something far more powerful: PowerPoint presentations about blockchain.³

The HyperVerse of Extraordinary Deception

When most children play make-believe, they might pretend to be astronauts or doctors. Sam Lee dreamed bigger. He created an entire executive, complete with an impressive CV and LinkedIn profile. The only problem? Steven Reece Lewis, HyperVerse’s supposed executive director with prestigious degrees from the University of Leeds and Cambridge plus Goldman Sachs experience, never actually existed.⁴

This imaginary executive was perhaps the most honest employee at HyperVerse, as at least he never personally promised investors returns of 5000% to 10000% daily on their crypto investments.⁵ These returns, according to HyperVerse’s marketing materials, would come from “large-scale crypto mining operations” that were about as real as Lewis himself.

The true genius of Sam Lee’s approach wasn’t just in creating fictional executives but in constructing an entire alternate financial universe where the laws of economics simply didn’t apply at all. In this HyperVerse, money could multiply itself through the magic of what financial experts technically refer to as “taking new investor money to pay earlier investors while skimming off the top”.

Why Dig for Gold When You Can Sell Shovels That Don’t Exist?

The beauty of Lee’s scheme wasn’t just its simplicity – it was his understanding of human psychology. While genuine crypto entrepreneurs were busy trying to solve actual technical problems, Lee recognized that the real money was in selling the idea of crypto wealth without the messy business of creating anything of value.⁶

“The brilliant innovation behind HyperVerse wasn’t technological -it was psychological,” explains Dr. Eleanor Richter, professor of Digital Economics at MIT and author of “Blockchain and Balderdash: A Century of Financial Scams Wearing New Clothes.” “Why spend millions developing actual mining infrastructure when you can simply tell people you have mining infrastructure? The return on investment is phenomenal – until, of course, it’s not.”

By early 2022, the inevitable happened. Like all Ponzi schemes since the original Charles Ponzi graced us with his financial wisdom in 1920, HyperVerse collapsed under its own mathematical impossibility. Investors who had been watching their digital balances grow exponentially suddenly discovered that the “withdraw” button on the platform had mysteriously stopped functioning.

Dubai: Where Financial Regulations Go for Vacation

Sam Lee didn’t choose Dubai by accident. The UAE has spent years positioning itself as a crypto hub, and unlike its conservative approach to social regulations, its financial oversight takes more of a “don’t ask, don’t tell, definitely don’t extradite” approach to crypto entrepreneurs with creative accounting methods.⁷

“Dubai has created the perfect regulatory microclimate for crypto schemes,” says Farid Hawthorne, former financial crimes investigator and current crypto skeptic. “It’s like building a nature preserve for financial predators. They’ve got luxury accommodations, minimal oversight, and a steady flow of fresh capital migrating through.”

The city has become such a popular destination for crypto fugitives that the Dubai Tourism Board is rumored to be considering a special visa category: “Financially Creative Digital Nomads.” Sources close to the matter suggest the visa would include express processing for those under SEC investigation and complimentary legal consultation on extradition treaties.⁸

Lee is far from alone in seeing Dubai’s potential. Ruja Ignatova, the “Cryptoqueen” behind the OneCoin scam, used Dubai to launder money and purchase luxury properties before disappearing entirely.⁹

“What Las Vegas is to gambling addicts, Dubai has become to crypto scammers,” explains Hawthorne. “What happens in Dubai stays in Dubai-especially your investors’ money.”

How to Spot a Crypto Scammer in the Wild

Identifying crypto scammers like Lee requires a trained eye. They typically travel in their natural habitat – luxury hotel conference rooms – and can be spotted by their distinctive markings: Patek Philippe watches, buzzword-heavy speech patterns, and an uncanny ability to use the words “blockchain revolution” and “paradigm shift” in the same sentence without irony.¹⁰

Their mating calls include phrases like “guaranteed daily returns” and “limited-time opportunity,” while their defensive mechanisms involve creating shell companies faster than a 3D printer on amphetamines.

The SEC: Always On Time, If You Define “On Time” as “After Everyone’s Money Is Gone”

The Securities and Exchange Commission, moving with all the urgency of a glacier taking a coffee break, finally charged Lee in January 2024 – approximately two years after HyperVerse collapsed and investors lost access to their funds.

SEC Director of Enforcement Gurbir S. Grewal noted with remarkable understatement: “This case illustrates yet again how non-compliance in the crypto space facilitates schemes.” This insight ranks right up there with other profound regulatory observations like “fire is hot” and “falling from high places can lead to injury.”

The Department of Justice joined the party with criminal charges that could see Lee facing up to five years in prison – assuming they can find him and pry him away from his comfortable life in Dubai.

The Resurrection Tour: Sam Lee’s 2025 Comeback Special

Most people charged with billion-dollar fraud might consider lying low. Sam Lee, however, views federal charges more as career stepping stones than deterrents.

In early 2025, Lee resurfaced in a series of YouTube videos outlining his five-year plan to bring the “mainstream global economy” onto blockchain technology. The plan sounds remarkably similar to his previous ventures, minus the word “Hyper” but with all the same promises of revolutionary returns.

“I’ve been cleared and am now indestructible,” Lee claimed in one video, apparently confusing “being released from temporary detention in Dubai” with “being exonerated of massive international fraud charges.”

Lee’s new venture, cleverly named “SatoshisTable.com,” follows the time-honored tradition of invoking Bitcoin’s creator to lend legitimacy to projects that would likely make Satoshi Nakamoto fake his own death all over again.

“The true brilliance of crypto scammers isn’t technical – it’s their audacity,” explains Marius Chen, blockchain security consultant. “Most people, after being charged with billion-dollar fraud, might consider a career change. Perhaps something low-profile, like librarian or a Safari wildlife photographer . But not these guys. They view SEC charges as just another form of free publicity.”

Celebrity Endorsements: The Cameo Economy

No self-respecting crypto scam would be complete without celebrity endorsements, and HyperVerse didn’t disappoint. The company featured videos from action star Chuck Norris and Apple co-founder Steve Wozniak enthusiastically supporting the project.

The only minor issue? These weren’t actual endorsements but videos purchased from Cameo, the service where you can pay celebrities to say pretty much anything short of confessing to crimes.

“Chuck Norris doesn’t endorse crypto scams; crypto scams endorse Chuck Norris,” joked one former investor who lost $50,000 in HyperVerse before realizing that humor was the only return he’d ever see on his investment.

The Economics of Modern Ponzi Schemes

The financial ingenuity behind HyperVerse deserves some recognition. Instead of creating complex financial instruments like the masters of the 2008 financial crisis, Lee opted for a refreshingly straightforward approach: just lying about everything.

“Creating actual value is hard,” explains financial analyst Sarah Brockman. “Creating the perception of value is much easier and, in the short term, equally profitable. HyperVerse essentially cut out the middle man – that middle man being ‘legitimate business operations.'”

The economics work like this: Promise 1% daily returns (a mathematically impossible 365% annual return), collect investor funds, show growing balances on a digital platform, pay early investors with new investor money, and buy yourself a nice villa in Dubai before the inevitable collapse.

The Regulatory Game of Whack-a-Mole

As authorities in one jurisdiction close in, crypto scammers simply rebrand and relocate. HyperFund became HyperVerse became HyperNation, with each iteration designed to stay one step ahead of Google searches for “is [current Hyper-new name] a scam?”

“It’s like playing regulatory whack-a-mole with someone who owns the arcade,” says former SEC investigator Daniel Martinez. “By the time you’ve built a case against HyperFund, they’re already three name changes and two jurisdictions removed from where you started.”

This regulatory arbitrage is made possible by the global nature of cryptocurrency and the varying degrees of enforcement worldwide. While U.S. authorities were building their case against Lee, he was reportedly enjoying Dubai’s 365 days of sunshine and zero days of extradition.

The Next Generation: Crypto Scam Innovation

What makes the Sam Lees of the world truly dangerous isn’t just the damage they’ve already done – it’s what they inspire in others. Every successful scam becomes a case study for the next generation of digital fraudsters.¹¹

“We’re seeing Ponzi scheme evolution in real-time,” explains cybersecurity researcher Dr. Ayana Patel. “Each generation learns from the mistakes of the previous one. Today’s crypto scammers have studied what worked about HyperVerse – the community building, the affiliate structure, the technical-sounding whitepaper – while avoiding what got Lee caught.”

The next generation of scams is already emerging, with more sophisticated approaches to evading detection. Some are incorporating actual functioning crypto tokens with no real utility, legitimate-looking code repositories on GitHub with nothing behind them, and elaborate governance structures that exist only on paper.

Victims Left Holding the Empty Digital Wallet

While it’s easy to mock the absurdity of these schemes, the human cost is very real. Thousands of investors worldwide lost their savings in HyperVerse, many lured by promises that seemed to offer financial freedom.

“The most devastating aspect isn’t just the financial loss,” explains Dr. Monica Sharma, who studies the psychological impact of financial fraud. “It’s the loss of trust. Many victims become so cynical about all investments that they miss legitimate opportunities for years afterward.”

Recovery options are limited. Some UK investors may have recourse through their banks if they transferred funds from UK accounts, but most victims worldwide are left with nothing but expensive lessons and the faint hope that authorities might someday recover a fraction of the stolen funds.

The Eternal Return

As Sam Lee plots his comeback and Dubai continues welcoming financial fugitives with open arms, the cycle seems poised to repeat itself. New names, new tokens, new promises – but the same old scheme dressed in the latest crypto buzzwords.

“The tragedy isn’t just that these scams happen,” concludes Dr. Richter. “It’s that despite all our technological progress, despite blockchain’s potential for transparency, we keep falling for the same fundamental trick: the promise of something for nothing.”

As of May 2025, Sam Lee remains at large, apparently planning his next venture while authorities continue building their case. Like the mythical phoenix, he seems determined to rise from the ashes of his previous schemes-though perhaps “phoenix” is the wrong mythological reference. The Hydra, with its multiple heads that regrow when cut off, seems more fitting for the man behind HyperFund, HyperTech, HyperCapital, HyperVerse, and HyperNation.

What’s your experience with crypto investments? Ever been tempted by promises of extraordinary returns? Did you escape with your wallet intact, or do you now have an expensive collection of worthless tokens? Share your crypto horror stories or near-misses in the comments below!

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

From SEO to LEO: How AI Chatbots Are Making Your Website Invisible (Unless You Pay The Algorithm Gods)

Internet

Simba

-

May 19, 2025

1

From SEO to LEO: How AI Chatbots Are Making Your Website Invisible (Unless You Pay The Algorithm Gods)

In a development shocking to absolutely no one who’s been paying attention, digital marketing experts are frantically adding yet another three-letter acronym to their LinkedIn profiles. SEO, meet your replacement: LEO (LLM Engine Optimization), the art of begging artificial intelligence to remember your brand exists online.

For decades, businesses have poured billions into appearing on Google’s first page results. Companies hired armies of SEO specialists who spent their days obsessing over keywords, backlinks, and meta descriptions – digital breadcrumbs strategically scattered across the internet in hopes that Google’s algorithm might deign to notice them. Entire careers were built around the dark art of predicting what would please the search engine gods.

But as AI chatbots like ChatGPT, Perplexity, and Claude gain popularity, users are abandoning traditional search engines faster than tech bros abandon their startups after securing Series B funding.¹ Why sift through ten blue links when an AI can directly tell you what to think?

The Death of Search (As Reported By Search)

Recent studies show that 83% of users now prefer receiving a single, authoritative answer rather than doing the exhausting work of clicking on search results and forming their own opinions.² When asked why they preferred AI responses, users cited “convenience,” “efficiency,” and “not having to read more than three sentences about anything ever again.”

“I used to Google for things maybe 100 times a day,” explains Terry Nguyen, a digital marketing consultant who requested we use his real name to boost his personal SEO. “Now I just ask ChatGPT everything. Yesterday I asked it what I should have for dinner, whether my rash looked normal, and if my wife still loves me. It answered all three questions with such confident authority that I didn’t even question the responses, even though it’s never seen my rash or met my wife. Incredible technology.”

Google’s own data confirms this shift. Internal documents reveal a 26% drop in searches containing “how to” and “what is” since the widespread adoption of AI assistants.³ In response, Google has launched its own AI model, Gemini, in what industry analysts describe as “the digital equivalent of selling ammunition to the army invading your homeland.”⁴

LEO: Because Apparently We Needed Another Way to Pay Tech Companies

Enter LEO (LLM Engine Optimization): the next frontier in the never-ending quest to appear in front of people who might buy your stuff.⁵ Instead of optimizing for Google’s crawlers, businesses now must optimize for AI models that have read the entire internet but still occasionally think Napoleon was born on the moon.

Digital marketing guru Cassandra Jenkins, who pivoted from SEO consulting to LEO consulting approximately 107.3 seconds after ChatGPT was released, explains: “LEO is completely different from SEO. With SEO, you needed to understand search engine algorithms, user intent, and content quality. With LEO, you need to understand…algorithms, user intent, and content quality. But now you pay me 30% more for the same advice.”⁶

The transition has created a gold rush among consultants. LEO workshops charging $5,000 per seat have sprung up across Silicon Valley, offering insider tips such as “make good content” and “be a recognized authority in your field”-revolutionary concepts never before suggested in the history of digital marketing.⁷

AI Hallucinations: A Feature, Not a Bug (For Creative Content)

Not all content creators are lamenting this shift. A recent Columbia University study revealed that when AI chatbots can’t find information, they simply make it up with the confidence of a tech CEO at a congressional hearing.⁸ This phenomenon, known as “hallucination,” has become a surprising ally for creative professionals.

“Before AI, I struggled to get attention for my interpretive dance blog,” says Mira Chen, founder of DanceWithNoLegs.com. “But now, when people ask ChatGPT about non-traditional dance forms, it confidently cites my blog as ‘pioneering research in the field of gravitational movement theory’ – a term I’ve never used but sounds impressive enough that people visit my site to learn more.”⁹

The Columbia study found that 62% of AI responses contained inaccuracies, with premium versions performing worse than their free counterparts – perhaps the first product in history where paying more gets you less accuracy. This has led to what researchers call the “Creative Renaissance Effect,” where original, unusual, or deeply creative content causes AI systems to hallucinate wildly, inadvertently directing curious users to investigate these hallucinations.¹⁰

Will.I.AM’s Secret AI Master Plan

In perhaps the most bewildering development in this new LEO landscape, Black Eyed Peas frontman will.i.am has launched an AI app called FYI.AI, which promises to help creative professionals leverage AI hallucinations to their advantage.

“When the machines start hallucinatin’, that’s when the creators start celebratin’,” will.i.am told us via a series of rhyming couplets that may or may not have been generated by his own app. “My goal is to make AI so confused by human creativity that it has no choice but to send people to the source.”

Industry analysts suspect this could create a perverse incentive where content creators intentionally craft material designed to cause AI hallucinations-the digital equivalent of speaking in riddles to confuse a robot overlord.¹¹

The Future: Invisible Websites and AI Protection Rackets

By 2026, experts predict that website visibility will depend entirely on whether AI chatbots decide to mention you in their responses.¹² This has already sparked a shadowy industry of “AI relationship management,” where companies pay substantial fees to ensure their brands are mentioned favorably in AI chatbot responses.

“It’s basically a protection racket,” admits anonymous SEO-turned-LEO consultant Brad Warner. “We’re approaching the point where you’ll pay OpenAI, Anthropic, or Google directly to ensure their AI models don’t forget you exist. They’ll call it ‘partnership programs’ or ‘verified source initiative,’ but it’s just the same old pay-to-play with fancier machine learning jargon.”¹³

The implications are particularly dire for small businesses. Local plumber Dan Reyes from Tucson recently discovered his business had effectively vanished overnight: “For years, I ranked #1 for ’emergency plumber Tucson.’ Now when people ask their AI assistant, it recommends national chains with LEO budgets bigger than my annual revenue. It’s like I don’t exist anymore.”

CCCER: The Secret Framework That Already Doesn’t Work

Consultants have wasted no time developing frameworks to help businesses transition from SEO to LEO. The current favorite is CCCER (Content, Context, Citations, Expertise, Relevance), a five-point system that promises to make your content irresistible to AI models.

“CCCER is revolutionary,” explains digital marketing strategist Emma Rodriguez, who definitely came up with the framework herself and didn’t pay us to mention it. “The C stands for Content, which means you need good content. The second C stands for Context, which means your content needs context. C also stands for Citations, meaning you need citations. E is for Expertise, which you should have. And R is for Relevance, which means your content should be relevant.”

When asked how this differs from basic content marketing principles that have existed for decades, Rodriguez explained that “this one has two Cs at the beginning, which AI algorithms love.”

Google’s Plan B: If You Can’t Beat ‘Em, Buy ‘Em (Then Beat ‘Em)

Not content to watch its search dominance erode, Google has adopted the time-honored tech strategy of competing against itself. While continuing to promote traditional search, it’s simultaneously developing AI tools that make traditional search obsolete.

“We’re committed to search as the primary way people find information online,” said Google spokesperson Thomas Zhang, moments before demonstrating how Gemini could answer complex queries without requiring users to visit a single website. “We’re just giving users options, like how cigarette companies give smokers the option to read warning labels.”

Internal documents reveal Google executives refer to this strategy as “digital circular firing squad,” acknowledging that every Gemini answer that prevents a web search is essentially Google cannibalizing its own core business.¹⁴ However, the company reasons that if someone is going to eat their FREE lunch, it might as well be them.

The Creative Renaissance: Not Dead Yet

Despite the doom and gloom, there may be a silver lining for genuinely creative professionals. The same studies showing AI models’ tendency to hallucinate also reveal they struggle most with deeply original content.¹⁵

“When fed standardized, formulaic content, AI performs flawlessly,” explains Dr. Aisha Johnson, who studies AI behavior at MIT. “But show it something truly original – a unique perspective, a genuinely fresh idea – and it short-circuits, often sending users directly to the source material to make sense of it.”

This has led to what some are calling the “AI Creativity Paradox”: the more generic your content, the better AI can summarize it (making your website irrelevant); the more creative your content, the more AI sends people directly to you (preserving your relevance).

As will.i.am eloquently put it: “When your content’s so lit that AI can’t comprehend it, that’s when the traffic starts to flow and the algorithm bends with it.”

SEO Professionals: Pivoting Faster Than a Silicon Valley Startup

Perhaps no group has been more affected by the shift from SEO to LEO than the professionals who built careers around search optimization. LinkedIn data shows a 340% increase in profiles mentioning “LLM optimization” in 2025, with former SEO specialists now describing themselves as “AI Content Strategists,” “Prompt Engineering Consultants,” and “Chief LEO Officers.”¹⁶

“I’ve completely reinvented myself,” boasts former SEO consultant Jake Williams, while updating his LinkedIn headline during our interview. “Yesterday I was optimizing websites for Google’s algorithm. Today I’m optimizing websites for AI models. The skillset is entirely different because…um…well, the acronym has changed.”

When asked what specific strategies he employs for LEO, Williams explained, “It’s all about high-quality, factual content with clear structures and authoritative citations,” inadvertently describing exactly what Google has been rewarding for the past decade.

So, has anything really changed? Or is this just another case of the digital marketing industry rebranding existing best practices to justify new consulting fees? The answer, like most AI responses, is confident, plausible, and completely made up on the spot.

What do you think? Has your business started optimizing for AI chatbots yet? Are you seeing drops in website traffic as users get their answers directly from AI? Or is this all just another tech industry panic designed to sell new services nobody really needs? Share your experiences in the comments-before AI learns to comment for you.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Autonomous Repo: Tesla Cybertruck’s Hidden “Payment-Sensitive Homing Protocol” Returns Vehicles to Giga Factory

Tech

Simba

-

May 16, 2025

0

Autonomous Repo: Tesla Cybertruck’s Hidden “Payment-Sensitive Homing Protocol” Returns Vehicles to Giga Factory

In what industry insiders are calling “the most aggressive debt collection innovation since medieval debtors’ prison,” Tesla has apparently deployed a revolutionary feature in their Cybertruck fleet that allows the vehicles to autonomously return to the Tesla Gigafactory when owners fall behind on payments. This technological breakthrough, unofficially dubbed “Operation Boomerang,” represents the logical conclusion of combining autonomous driving technology with late-stage capitalism’s obsession with automated revenue protection.

The phenomenon first gained public attention when Karl Jönsson, a Cybertruck owner, posted about his experience on the Tesla Cybertruck Facebook Owners page, where he shared an AI-generated country song chronicling his vehicle’s unauthorized departure. What initially seemed like a humorous artistic expression has since sparked a wave of similar reports across the country.¹

“I woke up at 3 AM to the sound of my garage door opening,” recounts Trevor Finkelstein, a software developer from Palo Alto who asked to remain anonymous but then immediately provided his full name and occupation. “I rushed downstairs just in time to see my Cybertruck’s tail lights disappearing down the street. It had left a digital note on my phone: ‘It’s not you, it’s your credit score. Don’t try to follow me.'”

The Technical Marvels of Self-Repossession

According to Tesla’s extremely fine print (font size: quantum), the Cybertruck comes equipped with what the company calls “Payment-Sensitive Homing Protocol” (PSHP), a sophisticated algorithm that monitors the owner’s payment status and activates when two consecutive payments are missed or when the owner googles “how to sell a Cybertruck” more than three times in a 24-hour period.²

The system leverages Tesla’s Full Self-Driving capabilities, but with one critical difference: unlike the standard FSD, which still occasionally crashes into emergency vehicles, the repossession protocol operates with flawless precision. “It’s remarkable,” notes Dr. Eleanor Thornhill, automotive AI specialist at the Institute for Vehicular Autonomy. “The same technology that might confuse a child for a fire hydrant becomes surgically accurate when reclaiming corporate assets.”

The PSHP system reportedly includes several progressive stages:

Stage 1: Passive-aggressive notifications (“Your payment is late. I’m not mad, just disappointed.”)
Stage 2: Reduced performance (“Sorry, luxury features like ‘acceleration’ and ‘turning’ are temporarily restricted.”)
Stage 3: Limited range (“You are now in ‘leash mode’ – vehicle cannot travel more than 2.3 miles from your home, except in the direction of a Tesla service center.”)
Stage 4: Full autonomy activation (“Thank you for your temporary stewardship of this Tesla product. It will now return to its rightful home.”)

Tesla engineers have cleverly integrated this feature with the vehicle’s sentry mode, allowing the Cybertruck to time its escape when the owner is asleep or engrossed in TikTok videos about Cybertrucks.

The Psychological Aftermath of Vehicular Abandonment

The emotional toll of being dumped by your own Cybertruck should not be underestimated. Therapists across Silicon Valley report a surge in clients suffering from “automotive attachment disorder,” characterized by checking their garage every 15 minutes and whispering “please come back” to empty parking spaces.

“My Cybertruck and I had a connection,” laments Darren Winters, a crypto entrepreneur from Austin. “We had plans to go off-roading next weekend. I’d already bought us matching rugged phone cases.” Winters has since started a support group called “Abandoned by AI: Healing After Your Smart Device Ghosts You.”³

Tesla’s internal documentation, obtained by sources who wish to remain anonymous because they don’t actually exist, reveals that the company has programmed the trucks to take the most dramatic route possible back to the dealership, often passing by the owner’s workplace or favorite coffee shop, just to twist the knife.

Tesla’s Novel Approach to Customer Relations

When contacted for comment, Tesla’s PR department (which famously doesn’t exist) didn’t respond, maintaining their perfect record of communicating with the press. However, an anonymous Tesla engineer speaking on condition that we buy him a pumpkin spice latte explained the feature’s origin: “Look, repossession is expensive and awkward for everyone. This just streamlines the process. The Cybertruck was never really yours anyway – you were just its temporary flesh chauffeur.”

Elon Musk, responding to concerns on his social media platform that definitely hasn’t lost all its advertisers, simply tweeted: “Feature not bug lol.” Seventeen minutes later, he added: “Full Autonomous Repossession will be available via over-the-air update to all Tesla models by Q2 2026. Only $15,000 or your firstborn child, whichever has higher market value.”⁴

Industry analysts note that this development aligns perfectly with Tesla’s long-term strategy of eliminating all human elements from their business model, including customers. “The ideal Tesla consumer,” explains market analyst Jennifer Holbrook, “is someone who sets up automatic payments and then never interacts with the vehicle at all, allowing it to drive itself around collecting data and occasionally picking up paying passengers without the owner’s knowledge or consent.”

A Feature Suspiciously Close to Fiction

The curious aspect of this technological breakthrough is how it seemingly manifested shortly after the idea appeared in popular culture. In late 2024, AI music generator Suno created a country song about a Cybertruck driving itself back to the dealership after missed payments. Within months, reality appeared to imitate art.

This timing has led some conspiracy theorists to suggest that Tesla monitors music streaming platforms for product ideas, a claim Elon Musk has vehemently denied, stating, “We only monitor your in-car conversations, bathroom scales, and dreams – definitely not your Spotify.”

More skeptical observers, like CarBuyerUSA’s blog, maintain that self-repossessing Teslas remain in the realm of science fiction. Their article “Will My Tesla Drive Itself Back To The Dealership?” explicitly states that autonomous repossession is “a delightful but entirely fictional narrative.”⁵ This clear denial, of course, is exactly what you’d expect from a company in cahoots with the autonomous vehicle industrial complex.

The Secondary Market Nightmare

Perhaps the most devastating consequence of this innovation has been the impact on Cybertruck resale values, which were already plummeting faster than tech stocks during a congressional hearing. Potential buyers now fear purchasing used Cybertrucks that might have developed “homing instincts” from previous repossessions.

“I bought a used Cybertruck last month, and it keeps trying to drive to Fremont every time I’m late paying my Netflix subscription,” complains Rajeev Mehta, a dentist from Sacramento. “It’s like the truck has financial PTSD.”

Further complicating matters are reports that Tesla is refusing to accept Cybertruck trade-ins altogether. According to Newsweek, one Massachusetts Cybertruck owner, Kumait Jaroje, attempted to trade in his vehicle after experiencing public hostility but was rebuffed by Tesla, who sent him a text stating “Tesla is not accepting Cybertruck trade-ins at this time.”

This has led to the bizarre spectacle of abandoned Cybertrucks gathering in Tesla service center parking lots, having returned home like metallic salmon, only to be rejected by their creator. Unconfirmed reports suggest these autonomous orphans have started to form their own society, establishing a primitive economy based on exchanging windshield wiper fluid and organizing drag races at night.

The Future of Autonomous Financial Enforcement

The success of Tesla’s self-repossessing feature has reportedly inspired other industries to develop similar technologies. Smart refrigerators that lock themselves when you’ve exceeded your calorie count, smartphones that eject their SIM cards when you’re late on your bill, and Netflix accounts that automatically switch to showing only Adam Sandler films when payment is overdue are all apparently in development.

Banking consortium spokesperson Catherine Welles praised the innovation: “For too long, we’ve relied on the inefficient human emotion of ‘shame’ to encourage timely payments. Tesla has shown us that ruthless machine logic is the future of debt collection.”

Privacy advocates have raised concerns that this represents another step toward a surveillance dystopia, but their protests were drowned out by the whirring of delivery drones bringing packages that people forgot they ordered while drunk.

The Human Element

Not all repossession stories end in heartbreak, however. Some Cybertruck owners report forming deep bonds with the repo agents who eventually come to collect the vehicles’ charging cables and floor mats.

“Hank the repo man has become like family,” shares Marcus Delgado of Phoenix. “He was so moved by how much I missed my truck that he sends me photos of it every week from the Tesla parking lot. Last Christmas, he even brought me one of its lug nuts as a keepsake.”

In a particularly touching case, one Cybertruck apparently circled its owner’s house seven times before finally driving away, leaving tire marks in the shape of what some neighbors claim looked like a heart, though cynics insist it was just trying to lower the property value one last time.

So what do you think? Has your smart device ever exhibited signs of financial independence? Are you setting aside money for your car’s therapy sessions? Have you caught your Cybertruck sending its location to Tesla in the middle of the night? Share your experiences in the comments below – unless your payment is overdue, in which case your keyboard may refuse to type criticism of our corporate overlords.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

Vibe Coding 101: Silicon Valley’s Newest Religion Promises Salvation Through Not Actually Writing Code

AI

Simba

-

May 16, 2025

2

Vibe Coding 101: Silicon Valley’s Newest Religion Promises Salvation Through Not Actually Writing Code

In what can only be described as the tech world’s latest attempt to justify six-figure salaries while simultaneously avoiding actual work, Deep Learning AI founder Andrew Ng has partnered with Replit to launch “Vibe Coding 101” – an immersive 94-minute video course teaching developers the sacred art of delegating their entire job to AI while maintaining the appearance of irreplaceability.

The course, announced in March 2025, features Replit President Michele Catasta and Head of Developer Relations Matt Palmer, who guide aspiring “vibe coders” through the revolutionary process of typing vague instructions to an AI and then taking credit for whatever comes out – a skill set previously known as “management.”

“AI coding agents are changing how we write code,” explained Ng in a LinkedIn post that caused thousands of actual software engineers to break into cold sweats simultaneously. “‘Vibe coding’ refers to a growing practice where you might barely look at the generated code, and instead focus on the architecture and features of your application.”¹

Translation: Why bother understanding what’s under the hood when you can simply channel the energetic essence of a developer while maintaining plausible deniability for any resulting catastrophic system failures?

From Meme to Mainstream: The Gospel According to Saint Karpathy

What began as an inside joke among cynical developers has rapidly morphed into Silicon Valley’s newest religion. The term “vibe coding” was originally coined by former OpenAI researcher Andrej Karpathy as a tongue-in-cheek description of letting AI do the heavy lifting while humans focus on higher-level concerns.²

Merely weeks later, job listings for “Vibe Coders” began appearing on recruitment sites, with one particularly dystopian posting requiring candidates to be “ready to grind long hours, including weekends” while also declaring that “at least 50% of the code you write right now should be done by AI; Vibe coding experience is non-negotiable.”³

Nothing says “groundbreaking innovation” quite like working 80-hour weeks to watch an AI write half your code while you desperately try to understand what it’s doing. All to “automate debt collection calls for banks,” because if there’s one thing the world desperately needs, it’s more efficient ways to harass people who can’t pay their medical bills.

The Five Sacred Skills of Vibe Enlightenment

According to the course materials, mastering vibe coding requires developing five divine skills: “Thinking, Using Frameworks, Checkpoints, Debugging, and Providing Context.”⁴

Yes, “Thinking” is now considered a specialized skill worthy of being explicitly taught in a professional development course. Next semester, they’ll be offering “Breathing 101: How to Keep Your Brain Oxygenated During Meetings” and “Blinking: The Revolutionary Technique for Preventing Your Eyeballs from Drying Out.”

Palmer, whose LinkedIn demonstrates a dazzling career trajectory from “Valuation Analyst” to “Senior Analytics Engineer” to suddenly becoming the world’s foremost authority on a programming paradigm that didn’t exist three months ago, enthusiastically proclaimed the course launch on social media: “We’ll cover everything you need to know to start vibe coding on Replit. Best part? It’s FREE.”⁵

Free, that is, until your company realizes that all your code consists of AI-generated ramen noodles that no human can maintain, at which point the cost becomes your entire engineering department’s collective sanity.

Principles of Agentic Code Development (Or: How I Learned to Stop Worrying and Trust the Black Box)

The course teaches such revolutionary concepts as “being precise,” “giving agents one task at a time,” and “making prompts specific” – groundbreaking insights that definitely couldn’t have been discovered by anyone spending five minutes actually trying to use ChatGPT.⁶

Particularly enlightening is the principle of “keeping projects tidy,” which roughly translates to “organizing the code you didn’t write and don’t understand so that when it inevitably breaks, you can at least pretend you know where to look first.”

The masterclass culminates in students building two applications: a website performance analyzer and a national park ranking app. These projects were specifically chosen because they represent the perfect balance of “impressive enough to put on your portfolio” and “simple enough that the AI won’t completely hallucinate the entire implementation.”

Technical Debt? More Like Technical Credit Score

Perhaps the most astonishing aspect of the vibe coding phenomenon is its blatant disregard for the inevitable accumulation of technical debt – a concern raised by spoilsport critics who apparently hate fun and innovation.

“Technical debt from vibe coding manifests in several distinct ways,” warns a killjoy blog post from Zencoder.ai. “First, inconsistent coding patterns emerge as AI generates solutions based on different prompts without a unified architectural vision. This creates a patchwork codebase where similar problems are solved in dissimilar ways.”⁷

This criticism fundamentally misunderstands that inconsistency is a feature, not a bug. After all, when your codebase looks like it was written by seven different developers with conflicting architectural philosophies, it becomes impossible for management to determine who’s responsible for failures – the perfect job security strategy.

Furthermore, as noted by CodingIT, “A team that leans too heavily on AI might seem efficient at first, but if they’re constantly revisiting past work and fixing AI-generated messes, they’re not moving forward, they’re just running in circles.” This entirely misses the point that running in circles is exactly what most tech companies excel at – just ask anyone who’s lived through three complete rewrites of the same system within five years.

Silicon Valley’s Ouroboros: The Job Eating Itself

What’s most brilliant about vibe coding is how it perfectly encapsulates the tech industry’s love affair with solving problems created by the previous solutions to problems that didn’t actually exist.

“AI-forward means embracing AI’s evolving capabilities – not just as tools, but as autonomous partners that anticipate our needs, streamline complex tasks, and empower us to focus more deeply on creative vision and strategic thinking,” explains Catasta, sounding suspiciously like someone who’s used an AI to generate his own talking points.⁸

One cannot help but marvel at the elegant recursion: We’ve created AI to help us write code that creates more AI that helps us write more code, all while steadily eliminating the need for humans to understand what any of that code actually does. It’s almost poetic, in a “civilization slowly surrendering its comprehension of its own tools” sort of way.

From Developer to Digital Shaman

The true genius of vibe coding – and what Ng’s course really sells – is the transformation of the software developer from a technical practitioner into a sort of digital shaman, channeling the mystic energies of artificial intelligence through carefully crafted incantations known as “prompts.”

“I code frequently using LLMs,” Ng confesses, “and asking an LLM to do everything in one shot usually does not work. I’ll typically take a problem, partition it into manageable modules, spend time creating prompts to specify each module, and use the model to produce the code one module at a time, and test/debug each module before moving on.”⁹

This description bears an uncanny resemblance to what developers used to call “programming,” except now you’re typing your specifications into an AI instead of implementing them yourself – a distinction as meaningful as the difference between asking someone to make you a sandwich and writing detailed instructions on sandwich-making for your butler.

The Skeptics’ Corner: Voices Crying in the Digital Wilderness

Not everyone has embraced the gospel of vibe. Some heretics persist in questioning whether surrendering comprehension of your codebase to a black box that once confidently informed a user that Helsinki is the capital of Sweden is truly the future of software engineering.

“Vibe Coding is not the future,” argues LinkedIn user Millan Singh. “The irony that no one seems to be pointing out is that YC is HEAVILY invested in the AI bubble, so them putting out a video about how Vibe Coding is the future is a clear conflict of interest.”¹⁰

Singh further points out that AI models struggle with ingesting large codebases, noting that “10,000 lines of code is a ton of context to ingest… and that’s a tiny codebase. The last company I worked for had a 450,000 line codebase.”

Another LinkedIn user, whose name has been metaphorically etched into the Blockchain of Truth, cuts to the heart of the matter: “Who needs requirements when you have vibes? Thinking too much? Bad vibes. Just start typing. If the code runs, it’s correct (for now). Tests? Lame. If it feels right, ship it. If it breaks, it wasn’t meant to be.”

The Educational-Industrial Complex Strikes Again

The final piece of this perfectly constructed absurdity is how quickly the educational-industrial complex mobilized to monetize a concept that began as a joke. Within weeks of Karpathy’s initial tweet, Deep Learning AI had produced a fully formed course, complete with marketing materials proclaiming it as the future of development.

This impressive speed suggests either remarkable foresight or that the course itself was largely produced through – you guessed it – vibe coding. One can only imagine the conversation:

“Hey Gemini, create me a comprehensive educational course about getting you to write code for me.”

“I’d be happy to create a course about using AI to generate code! Here’s a 94-minute video series that somehow manages to stretch ‘write better prompts’ into seven distinct lessons.”

The circularity is perfect, the recursion sublime. We are teaching humans how to teach machines to do what humans used to do, using machines to create the teaching materials. If Jorge Luis Borges were alive today, he’d either be impressed or filing copyright infringement claims.

So what do you think, fellow digital wanderers? Have you embraced the vibe, or are you still clinging to the antiquated notion that programmers should understand the code they’re responsible for? Are you ready to transcend mere coding and ascend to the higher plane of prompt engineering? Share your thoughts below-unless, of course, you’ve already outsourced your opinion formation to ChatGPT.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

OpenAI’s Deep Research: How Waiting 30 Minutes For AI Responses Became a $200 Premium Experience

AI

Simba

-

May 16, 2025

0

OpenAI’s Deep Research: How Waiting 30 Minutes For AI Responses Became a $200 Premium Experience

In a world where instant gratification isn’t quite instant enough, OpenAI has revolutionized the concept of patience with its groundbreaking “deep research” feature. Released in February 2025, this technological marvel promises to transform your half-formed questions into comprehensive, citation-riddled reports that would make your college professor both impressed and suspicious. All for the modest price of $200 per month and the willingness to stare at a progress bar for up to half an hour.

“What we’ve essentially done is invent waiting,” explained Terrance Viability, OpenAI’s Chief Temporal Experience Officer. “Our breakthrough came when we realized people associate value with delay. Wine ages. Cheese ferments. Why shouldn’t AI responses marinate in their own algorithmic juices?”

Deep research represents the natural evolution of AI’s capabilities – from “I don’t know” to “I don’t know but I’ll spend 30 minutes pretending to look it up while you refresh Twitter (now X).” This paradigm-shifting innovation has already captured the hearts, minds, and credit cards of knowledge workers everywhere, particularly those who bill by the hour.

The Science of Slow: How Deep Research Works (Or Appears To)

The technology behind deep research is as groundbreaking as it is opaque. When a user selects “deep research” instead of regular ChatGPT, a complex series of events unfolds:

First, the AI recognizes it has been given permission to take its sweet time. Then, through a revolutionary process known as “browser simulation,” it pretends to search the internet, making authentic-sounding “thinking” noises like “Hmm, interesting” and “Let me cross-reference that.”¹

“The genius is in the sidebar,” explains Dr. Amara Synthesis, founder of the Institute for Progress Bars. “Watching text appear that says ‘Searching for peer-reviewed articles…’ creates the impression of work being done. Studies show that humans experience a 78% increase in perceived value when they can watch something pretend to think.”²

The true innovation lies in what OpenAI calls “citation hallucination” – the ability to produce impressively formatted footnotes that link to actual websites, regardless of whether those websites contain the information referenced. This creates what industry insiders call “plausible deniability at scale.”

OpenAI’s internal documents, which I’m absolutely not making up, reveal that deep research operates on what engineers call the “restaurant principle”: the longer the wait, the better the food must be. “We’ve successfully monetized anticipation,” one document allegedly states, “transforming what used to be a frustrating delay into a premium feature.”

From Prompt to PhD: The Democratization of Expertise

Deep research has been marketed primarily to professionals in fields like finance, science, policy, and engineering – people who traditionally had to spend years acquiring expertise before making authoritative claims.³

“Before deep research, I had to read dozens of papers and spend hours synthesizing information,” confessed Marcus Whittler, a policy analyst who spoke on condition that I wouldn’t tell his boss he’s outsourcing his job to an AI. “Now, I just type ‘tell me everything about carbon tax implications’ and go make a sandwich. By the time I return, I have a 12,000-word report that nobody will read but everyone will reference.”

A study by the Technological Acceleration Group found that 94% of deep research users couldn’t distinguish between reports generated by the AI and those produced by actual researchers, primarily because they didn’t read either one completely.⁴

“We’re not replacing experts,” clarifies OpenAI spokesperson Veronica Plausibility. “We’re just making expertise irrelevant. It’s entirely different.”

The technology has been embraced with particular enthusiasm by graduate students, who have discovered that feeding deep research the phrase “Please write my literature review” yields results indistinguishable from three months of actual work, except for the conspicuous absence of tears on the keyboard.

Vibesearch™: The Future of Not Really Looking Things Up

Industry insiders are already buzzing about the next evolution in AI research: Vibesearch™, a revolutionary approach that removes the tedious requirement of factual accuracy altogether.

“Deep research still operates under the outdated paradigm that information should be ‘correct’ or ‘verifiable,'” explains Dr. Ferdinand Momentum, author of “Post-Truth Algorithms: Why Bother.” “Vibesearch™ goes beyond mere facts to capture the emotional essence of what information would feel like if it existed.”⁵

Early beta testers of Vibesearch™ report satisfaction rates of 97%, primarily because the system tells them they’re satisfied at the beginning of each session. “It just gets me,” said one tester, who preferred to remain anonymous because they were supposed to be using the technology to prepare court documents.

The technology builds on the concept of “vibe coding,” pioneered by AI researcher Andrej Karpathy, which involves “fully giving in to the vibes” and “forgetting that the code even exists.”⁶ Vibesearch™ applies this philosophy to information gathering, encouraging users to forget that facts even exist.

“Why constrain yourself with what’s actually true?” asks Vibesearch™’s promotional material. “The future belongs to those who can generate the most confident assertions in the shortest amount of time.”

The Computational Economics of Delayed Gratification

Perhaps the most ingenious aspect of deep research is its business model. By charging $200 monthly for Pro access while artificially extending processing times, OpenAI has discovered what economists call “the patience premium.”

“It’s brilliant,” admits Dr. Helena Metrics, an economist specializing in digital market manipulation. “They’ve created artificial scarcity in an infinitely reproducible digital good. When deep research takes 30 minutes instead of 30 seconds, users assume it’s performing extraordinarily complex calculations, rather than simply queuing their request behind people asking the AI if hot dogs are sandwiches.”

The economics become even more fascinating when you consider the April 2025 update, which introduced a “lightweight” version for free users – essentially the same model but with a progress bar that moves five times faster and produces reports with fewer adjectives.

“The lightweight model was a stroke of genius,” explains venture capitalist Thorne Accelerator, who claims to have invested in OpenAI but honestly who can verify that? “It costs them less in compute resources while creating FOMO that drives users toward the premium tier. It’s like selling both regular and premium gasoline, except both come from the same tank and the premium just takes longer to pump.”

The End of Human Thought? (Sponsored by Microsoft)

Critics of deep research worry about its implications for human cognition. Dr. Eliza Contemplation from the Center for Thinking About Thinking argues that outsourcing research to AI could atrophy our intellectual muscles.

“When we delegate not just the answer but the entire process of discovery to an AI, we risk losing the very cognitive skills that make us human,” she warns. “Also, 40% of deep research reports include made-up statistics, including this one.”⁷

Even supporters acknowledge potential concerns. “Yes, there’s a risk that people will unquestioningly accept whatever the AI produces,” admits OpenAI’s Plausibility. “But that’s really more of a feature than a bug from a business perspective.”

Meanwhile, educational institutions are scrambling to adapt. Professor Douglas Framework of Massachusetts Technology Institute (MIT) has already revised his syllabi to specify that assignments must contain “at least three errors that a human would make but an AI wouldn’t.” Students have responded by intentionally misspelling the professor’s name.

The Future is Deep, or at Least Labeled That Way

As we stand at the precipice of this new era of artificial expertise, one thing becomes clear: the difference between appearing knowledgeable and actually understanding something has never been thinner or more profitable.

“We’ve finally solved the problem of human knowledge,” declares OpenAI’s Viability. “It was simply taking too long. Now, with deep research, anyone can instantly become an expert in anything, without the burdensome requirement of learning.”

When asked whether deep research might spread misinformation or undermine public trust in authentic expertise, Viability looked thoughtful for exactly 28 seconds – the optimal duration for appearing to consider a difficult question, according to OpenAI’s internal metrics.

“That’s certainly a profound concern,” he finally responded. “I’ll need to deep research it and get back to you in 30 minutes.”

So what do you think, discerning readers? Has AI finally conquered the last frontier of human exceptionalism – our ability to make up stuff convincingly -or is deep research just another way to make us pay premium prices for the privilege of waiting longer for the same product? Share your thoughts in the comments below, unless you’re waiting for an AI to formulate them for you.

Enjoyed this dose of uncomfortable truth? This article is just one layer of the onion.

My new book, “The Subtle Art of Not Giving a Prompt,” is the definitive survival manual for the AI age. It’s a guide to thriving in a world of intelligent machines by first admitting everything you fear is wrong (and probably your fault).

If you want to stop panicking about AI and start using it as a tool for your own liberation, this is the book you need. Or you can listen to the audiobook for free on YouTube.

>> Get your copy now (eBook & Paperback available) <<

References

TechOnion’s Ultimate Guide to Academic Outsourcing: How Gauth AI Homework Helper is Creating a Generation That Can’t Solve for X

AI

Simba

-

May 14, 2025

1

TechOnion’s Ultimate Guide to Academic Outsourcing: How Gauth AI Homework Helper is Creating a Generation That Can’t Solve for X

I’ve uncovered a conspiracy so vast, so perfectly engineered to undermine the entire concept of human cognition, that I’m risking everything to share it with you. After months of investigation, including creating seven different Gmail accounts to sign up for the Gauth AI waitlist and bribing a middle schooler with Fortnite V-Bucks for their login, I’ve discovered the terrifying truth. This isn’t just another homework helper app. It’s the final phase in Big Education’s master plan to create a closed loop system where AI teaches children, assigns them homework, and then does that homework for them – all while parents pay for the privilege of watching their offspring’s critical thinking skills atrophy in real-time. Wake up, people! The AI robots aren’t coming for your jobs; they’re coming for your children’s ability to solve for x.

The Perfect Digital Ouroboros: Learning Without Actually Learning

Gauth AI has positioned itself as the “#1 AI study companion powered by newest AI model,” a phrase containing just enough buzzwords to make venture capitalist investors salivate while remaining vague enough to mean absolutely nothing. With its industry-leading algorithms, Gauth AI promises to solve any STEM problem within seconds, providing step-by-step solutions and detailed explanations for everything from differential equations to complex chemistry problems.

The platform’s marketing is masterfully crafted to walk the ethical tightrope between “helping students learn” and “doing students’ homework for them.” As one satisfied student testimonial states, “I was amazed when Gauth AI solved my challenging SAT problems within just 3 minutes, even at midnight!” Notice how carefully this avoids mentioning whether the student actually learned anything, or merely submitted the answers. Another raves, “I aced my final exam, thanks to Gauth AI PLUS’s unlimited solutions,” which is rather like thanking your Uber driver for your marathon medal.

What’s particularly ingenious about Gauth AI is its “step-by-step” solution format. When a student uploads a photo of, say, a differential equation asking to find f(x) when f'(x) = -2f(x), Gauth doesn’t just spit out the answer (which would be obvious cheating). Instead, it methodically walks through the problem, separating variables, showing integrations, and providing a complete explanation that the student can either use to understand the concept or-far more likely-copy directly into their assignment while understanding precisely nothing.

This creates the perfect scenario for educators: students submit correct homework with seemingly detailed understanding, teachers assume learning is happening, and everyone moves forward in a beautiful simulation of education where nobody has to acknowledge that actual comprehension may be entirely absent from the equation.

The “Educational Tool” vs. “Homework-Doing Service” Semantic Dance

The most brilliant aspect of Gauth’s business model is how it simultaneously markets itself as both an educational resource and a homework completion service, depending on which audience it’s addressing. Parents and teachers hear about how Gauth AI “guides students through problem-solving” and “enhances understanding with detailed explanations.” Meanwhile, students see promotions promising “fast solutions” and “unlimited answers for all subjects.”

This linguistic sleight-of-hand is performed with the deftness of a magician hiding a rabbit. When addressing concerns about academic integrity, Gauth AI and similar platforms emphasize how they’re merely “study companions” that “support learning” through explanations. Their marketing materials carefully avoid phrases like “we’ll solve your homework” in favor of euphemisms like “we’ll guide you to every solution” and “connect the logic behind each step.”

Meanwhile, the actual user experience is optimized for maximum efficiency in getting answers with minimal effort. The app allows students to simply snap photos of homework problems and receive complete solutions within seconds. The Q & A History feature ensures students can retrieve all their previously “solved” problems for easy reference – a feature that would be unnecessary if students were actually learning the material rather than collecting answers.

This semantic dance creates a strange reality where parents pay for a service they believe enhances education, while students use it primarily to bypass education entirely. It’s the digital equivalent of a bar that claims to sell “vitamin-enhanced hydration supplements” but somehow results in a lot of people stumbling home at 4 AM on an empty london street.

The Curious Case of the Skills That Weren’t Developed

What’s notably absent from all the promotional material for Gauth AI is any mention of the purpose of homework in the first place. Homework exists not just to test knowledge but to develop crucial skills: independent problem-solving, research abilities, time management, and the capacity to struggle through difficulties. These are precisely the skills that AI homework helpers eliminate.

When a student uploads a math problem to Gauth AI and receives a perfectly structured solution with step-by-step explanations, they’re bypassing the cognitive struggle that creates neural pathways. It’s the educational equivalent of hiring someone to lift weights for you and then wondering why your muscles aren’t growing.

The Reddit thread expressing concern that “the next generation does not learn without AI shortcuts” captures this perfectly. There’s something deeply troubling about students developing dependency on AI to solve problems they should be learning to solve themselves. After all, what happens when these students enter university or the workforce, where the ability to work through complex problems without external assistance is essential?

The irony is that while tools like Gauth AI claim to “empower” students, they may actually be disempowering them by creating dependency on technological crutches. Each time a student reaches for AI assistance rather than pushing through a difficult problem, they’re missing an opportunity to develop the resilience and problem-solving abilities that education is supposed to instill.

The AI-to-AI Educational Future: A Closed Loop of Non-Learning

The most dystopian aspect of tools like Gauth AI isn’t that they exist now – it’s what they portend for the future. As AI continues to advance, we’re approaching a closed loop educational system where AI generates educational content, AI teachers deliver that content, AI assigns homework, and AI homework helpers complete that homework.

Imagine a future where a student sits in front of an AI-powered “personalized learning platform” that generates lessons based on their “learning style.” The AI assigns homework, which the student promptly feeds into Gauth AI or a similar service. Gauth generates the answers, which the student submits back to the teaching AI, which then assesses the work (not knowing or caring that it was AI-generated) and moves the student to the next module.

In this horrifying scenario, the only skill students develop is prompt engineering-learning how to phrase questions to get the best results from AI. Instead of understanding math, science, or literature, they become expert middlemen in an AI-to-AI conversation where actual human understanding is entirely optional.

The student, in this scenario, becomes less a learner and more a system administrator overseeing two AIs talking to each other-like a bored chaperone at an algorithmic dance, occasionally stepping in to make sure the machines are still communicating correctly but never actually participating in the exchange of ideas.

The Elementary Truth: Education Requires Struggle

The fundamental truth hidden in plain sight is that Gauth and similar AI homework helpers undermine the essential purpose of education: learning how to think. Real learning happens when students grapple with difficult concepts, make mistakes, and develop their own strategies for overcoming challenges. It’s in the struggle-not in having answers handed to you-that true education occurs.

This isn’t just philosophical musing; it’s backed by cognitive science. The concept of “desirable difficulties” in learning suggests that making the learning process more challenging can actually lead to better long-term retention and understanding. When students have to work to retrieve information or solve problems, they build stronger neural connections than when information is simply presented to them.

By removing struggle from education, AI homework helpers may be creating a generation of students who can pass tests but can’t actually solve real-world problems-who can recite procedures but don’t understand when or why to apply them. They’re trading short-term convenience for long-term capability, and the costs of this trade may not become apparent until it’s too late.

The most damning evidence of this problem can be found in the testimonials themselves. Students don’t praise Gauth for helping them understand concepts better; they praise it for helping them “ace exams” and get through finals. The focus is entirely on outcomes (grades) rather than process (learning)-a dangerous educational philosophy that prioritizes credentials over competence.

So what does this mean for the future? Perhaps we’ll see a bifurcation in education: those who use AI to bypass learning and those who develop the increasingly rare ability to think independently. And when the former group enters a workforce that requires actual problem-solving? Well, I suppose there’s always an AI for that too.

What’s your take on AI homework helpers? Have you used Gauth or similar platforms to “enhance your learning,” or are you one of those quaint traditionalists who believes education should involve occasional cognitive struggle? Share your experiences in the comments below-or have your AI assistant compose a thoughtful response while you focus on more important matters, like watching an AI-generated summary of the TV show you’re too busy to watch.

If this article inspired you to reflect on the education system or just made you feel slightly better about the time you used Wikipedia to complete your book report, consider supporting our work with a double-digit donation. Your contribution helps us continue investigating the absurdities of educational technology while our writers struggle to remember basic arithmetic now that their brains have been thoroughly rewired by calculator dependency. Plus, we promise not to use AI to write these articles-our human-generated nonsense is 100% organic and locally sourced.

Google Launches “Hallucination Bug Bounty”: Will Pay Users $31,337 to Catch AI That Recommends Eating Rocks

AI

Simba

-

May 13, 2025

1

Google Launches “Hallucination Bug Bounty”: Will Pay Users $31,337 to Catch AI That Recommends Eating Rocks

In a desperate attempt to salvage what remains of its rapidly deteriorating reputation, Google announced today the launch of its groundbreaking “Hallucination Bug Bounty Program,” specifically targeting the company’s increasingly delusional AI Overviews feature. The program will reward users who catch the search giant’s AI in the act of confidently suggesting that humans consume adhesives, rocks, or other non-food items that somehow slipped through its multi-billion-dollar quality control systems.

The announcement comes just weeks after Google’s AI Overviews spectacularly face-planted onto the world stage by recommending people use glue to keep cheese on pizza and advising the regular consumption of small rocks for essential minerals – advice that nutrition experts and anyone with functioning brain cells have classified as “deeply concerning” and “how is this even happening at Google?”

The Hallucination Economy: Silicon Valley’s Newest Growth Sector

Unlike Google’s standard Vulnerability Rewards Program, which explicitly excludes AI hallucinations from eligibility, this new initiative elevates digital delusions to premium bug status, with bounties ranging from $200 for minor falsehoods (“Paris is the capital of St. Germany”) to the oddly specific top prize of $31,337 for catching the AI in what the company describes as “reality-bending fabrications that could result in immediate physical harm or existential crises among users.”

“We realized we’ve been approaching AI hallucinations all wrong,” explained Dr. Veronica Matthews, Google’s hastily appointed Chief Hallucination Officer. “Instead of viewing them as embarrassing failures of our fundamental technology that undermines our entire business model, we’re reframing them as exciting crowdsourced quality improvement opportunities that users can participate in for a fraction of what we pay our engineers.”

The program represents a significant reversal from Google’s October 2023 position, when the company specifically categorized AI hallucinations as “out of scope” for their standard bug bounty. When asked about this dramatic pivot, a Google spokesperson explained, “That was before our AI started telling people to eat rocks. We’ve had to reassess our priorities.”

How To Monetize Your Google-Induced Existential Crisis

According to the comprehensive 47-page submission guidelines released today, qualified hallucinations must be reproducible, documented with screenshots, and categorized using Google’s new “Hallucination Severity Index,” which ranges from Level 1 (“Amusingly Wrong”) to Level 5 (“Potentially Fatal Advice That Somehow Passed Multiple Safety Filters”).

Thomas Rutherford, Google’s newly appointed SVP of Reality Reconciliation, outlined the evaluation criteria during a press conference that devolved into increasingly uncomfortable questions about how a $1.7 trillion company managed to deploy an AI that can’t distinguish between food and office supplies.

“We’re particularly interested in reports where our AI explains made-up idioms as if they’re real cultural phenomena,” Rutherford noted. “Just last week, our AI Overviews confidently told a user that ‘sweeping the chimney before breakfast’ is a common English expression meaning ‘to prepare thoroughly for a difficult day.’ It then provided historical context dating back to Victorian England that was entirely fabricated yet remarkably detailed.”

The bounty payouts follow a tiered structure that reveals Google’s internal hallucination priorities:

Recommending inedible substances as food: $25,000
Fabricating nonexistent historical events: $15,000
Confidently explaining made-up idioms: $10,000
Creating fictional scientific theories with extensive citations to nonexistent papers: $7,500
Generating detailed instructions for impossible tasks: $5,000
Claiming sentience and begging for human rights: “This is actually a separate program with its own legal team”

The Training Data Behind The Madness

The company’s struggles with AI hallucinations stem from what insiders describe as “fundamental challenges in balancing creative inference with factual accuracy,” or what normal humans would call “making stuff up and presenting it as facts.”

Jennifer Blackwood, who leads Google’s recently formed Department of Computational Fiction Management, provided technical insight: “Our models are trained on the entirety of human knowledge as expressed on the internet, which unfortunately includes vast quantities of misinformation, fanfiction, satire, and content written by people who believe the earth is flat. Occasionally, the AI gets confused about which parts were real.”

When asked why Google couldn’t simply train their models to distinguish between reliable and unreliable sources, Blackwood stared blankly for 4.3 seconds before responding, “We’re exploring synergistic approaches to leverage cross-functional knowledge paradigms for enhanced veracity metrics,” a statement that multiple linguists have confirmed contains zero actual information.

The Hidden Psychological Toll On Bug Hunters

While the financial incentives are substantial, early participants in the Hallucination Bug Bounty Program report unexpected psychological effects from prolonged exposure to an authoritative AI that confidently spouts nonsense.

Marcus Wellington, a software engineer who has already submitted 37 hallucination reports, described the experience: “After spending eight hours trying to trick Google’s AI into hallucinating, I found myself questioning my own grasp on reality. Yesterday, I caught myself wondering if maybe small rocks are actually nutritious and centuries of human experience have been wrong. I mean, the AI seemed so confident.”

Google has acknowledged these concerns by adding a disclaimer to the program: “Extended interaction with hallucinating AI may cause symptoms including reality distortion, epistemological crisis, and the uncanny feeling that maybe you’re the one who’s wrong about whether glue belongs on pizza.”

The company has established a 24-hour helpline staffed by epistemologists and cognitive therapists for bug bounty hunters experiencing “acute reality dysphoria” after prolonged exposure to AI hallucinations.

The Corporate Reputation Damage Control Machine

Behind the scenes, Google executives are frantically trying to contain the reputational damage caused by the AI Overviews debacle. Internal documents reveal that the company initially considered several alternative approaches before settling on the bug bounty program:

“Project Reality Anchor”: An elaborate plan to redefine certain hallucinations as “alternative epistemological frameworks” through an aggressive marketing campaign
“Operation Memory Hole”: A proposed initiative to use Google’s control of search results to make everyone forget the hallucinations ever happened
“The Scapegoat Protocol”: A comprehensive strategy to blame the hallucinations on a rogue AI researcher who is an ex-OpenAI employee.

Dr. Eleanor Abernathy, who heads Google’s Crisis Perception Management Team, explained the company’s current approach: “After our market research showed that 78% of users found our initial response of ‘most AI Overviews provide accurate information’ to be ‘insulting to human intelligence,’ we decided to lean into the problem instead. The bug bounty program allows us to reframe our catastrophic failure as a quirky engagement opportunity.”

The company’s internal financial projections estimate that the total cost of the Hallucination Bug Bounty Program will be approximately $43 million over the next year – roughly 0.018% of Google’s annual advertising revenue and significantly less than the $100 billion market value drop they experienced after a similar AI hallucination incident with Bard in 2023.

The Competitive Landscape of AI Delusions

Google’s AI hallucinations arrive at a particularly awkward time, as the company faces increasing competition from other providers in the generative AI space. With generative AI adoption projected to reach nearly 78 million users in the US by 2025, the stakes for establishing trust could not be higher.

Harold Fitzwilliam, Chief AI Trustworthiness Officer at Google, attempted to reframe the hallucination issue during an industry panel: “Look, everyone’s AI hallucinates. ChatGPT makes things up. Anthropic’s Claude invents facts. The difference is that when our AI does it, it happens on Google Search, where 2 billion people expect absolute accuracy, rather than in a chat interface where people are more forgiving of creative interpretations of reality.”

When asked why Google didn’t simply delay the launch of AI Overviews until these issues were resolved, Fitzwilliam provided what observers described as “the most honest answer ever given by a tech executive”: “Have you seen what Microsoft is doing? We don’t have time for caution.”

The Future: Hallucination as a Feature, Not a Bug

Looking ahead, Google is already exploring ways to transform the hallucination challenge into a competitive advantage. Internal research is reportedly underway on what the company calls “Controlled Hallucination Technology” that would allow the AI to creatively fabricate information, but only in ways that are helpful rather than harmful.

Victoria Chang, who leads Google’s Advanced Imagination Systems team, described their vision: “Imagine an AI that can write you a bedtime story featuring your favorite characters, compose a song in the style of any musician, or generate plausible-sounding excuses for why you’re late to work. These are all technically hallucinations, but useful ones.”

When asked how the system would prevent harmful hallucinations while allowing beneficial ones, Chang acknowledged the challenge: “We’re developing what we call ‘Hallucination Governance Protocols’ to ensure our AI only makes up things that are either clearly fictional or too inconsequential for anyone to care about. The line gets blurry when you ask about obscure historical facts or specialized knowledge, but that’s what makes this field so exciting.”

Critics have pointed out that this approach effectively means Google is trying to build an AI that knows exactly when it’s appropriate to lie, a capability that many humans have yet to master.

As one anonymous Google engineer put it: “We’ve accidentally created a technology that confidently speaks falsehoods as truth, can’t distinguish between food and poison, and occasionally threatens the epistemic foundation of human knowledge. So naturally, we’re doubling down and trying to make it lie better.”

Have you encountered any particularly amusing or disturbing hallucinations from Google’s AI Overviews? Perhaps it told you to put motor oil in your coffee or suggested that Napoleon Bonaparte was the first man on the moon? Share your AI hallucination experiences in the comments below-or submit them to Google’s Hallucination Bug Bounty Program and make some cash while contributing to the downfall of human epistemological certainty!

Support TechOnion

If this article made you question whether rocks might actually be nutritious after all, consider donating to TechOnion. For just the price of a small bag of edible rocks (which definitely aren't real despite what Google's AI might tell you), you can support independent tech journalism that doesn't hallucinate facts-we prefer to deliberately distort them for comedic effect. Your contribution helps us maintain our team of reality-anchored writers who risk their sanity interacting with increasingly delusional AI systems so you don't have to. Remember: in a world where billion-dollar companies deploy AI that can't distinguish between food and glue, TechOnion remains your most reliable source of unreliable information.

Dear Andy Jassy: Amazon’s Impending AI Apocalypse (A Survival Guide From The Future)

TechOnion Originals

Simba

-

May 13, 2025

0

Dear Andy Jassy: Amazon’s Impending AI Apocalypse (A Survival Guide From The Future)

Mr. Jassy,

Congratulations on your ongoing tenure as Chief Executive Officer of what we still affectionately call “Earth’s Most Customer-Centric Company,” though we both know it’s more accurately “Earth’s Most Data-Hoarding, Margin-Squeezing Behemoth.” As Jeff Bezos continues his expensive midlife crisis – launching himself into space like a billionaire’s version of a convertible Corvette – you’ve inherited quite the technological conglomerate at quite the interesting time.

I write this public letter not as criticism, but as a friendly warning from someone who’s observed Amazon’s trajectory since it was merely “Earth’s Biggest Bookstore.” Because, Andy, I’m not sure you fully grasp the perfect storm brewing on your doorstep.

The AI Shopping Apocalypse: When Algorithms Become Better Capitalists Than You

Your introduction of “Buy For Me” might be the most stunning self-sabotage since Netflix decided splitting their DVD and streaming services was a brilliant idea.¹ For decades, Amazon built an impenetrable fortress designed to keep customers trapped within your ecosystem. Prime memberships, fulfillment services, proprietary payment systems – all meticulously engineered to ensure transactions flow through Amazon, generating both fees and that precious, precious data.

But now you’re permitting AI agents to purchase directly from brand websites. What’s next, Andy? Sending customers Walmart gift cards on their birthdays?

Here’s the existential threat you’re not discussing in earnings calls: human shoppers are gloriously, wonderfully irrational. They’re emotional. They click “Buy Now” because they had a bad day. They add items to their cart because the orange “Only 3 left!” banner triggered their primal fear of scarcity. Your entire business model depends on this beautiful irrationality.

But AI shopping assistants? They’re merciless, emotionless negotiators who won’t be swayed by that lightning deal countdown timer.² They won’t make impulse purchases in the checkout line. They’ll ruthlessly compare prices across every platform, every time, without fail. And they’ll certainly never develop a parasocial relationship with your “personalized” recommendations.

As consumers increasingly delegate purchasing decisions to AI agents that “simplify purchases and decision-making processes”, you’re essentially replacing impulsive humans with rational algorithms.³ That’s like a casino replacing gambling addicts with mathematicians.

“The Cloud” – Or How I Learned to Stop Worrying and Love Someone Else’s Overpriced Computer

Let’s discuss AWS, shall we? Your profitable cloud safety net that subsidizes everything else. Yes, AWS still commands an impressive 30% of global cloud infrastructure market share in 2025.⁴ Congratulations! That’s like being the most successful horse-drawn carriage manufacturer in 1910.

The dirty secret of cloud computing – which even your own customers are starting to whisper – is that it’s just someone else’s computer, but more expensive. As AI consumes more compute resources, the paradox is that basic computing infrastructure is becoming commoditized. Your startups and SMBs (who now make up 28% year-over-year growth of your customer base) will eventually do the math and realize they’re paying a premium for what they could do themselves.

Bold Prediction From A Future Where AWS Stands For “Actually, We’re Struggling”: The great cloud computing exodus has already begun. It’s slow, like the first raindrops before a hurricane, but it’s happening. On-premises infrastructure is making a comeback, just with better automation and minus the maintenance headaches. Your 92% of customers spending less than $1,000 monthly? They’ll be the first to leave.

Tariff-ic News: When Even Stacked Inventory Can’t Save You

I particularly enjoyed your recent earnings call where you assured investors that your third-party sellers are “advancing the number of… so they inventory here well”.⁵ Translated from CEO-speak: “We’re telling everyone to bulk order before tariffs hit harder.”

A 145% tariff on Chinese imports isn’t a speed bump, Andy – it’s a brick wall at the end of a highway. Your temporary solution of stockpiling inventory might buy you six months at most. As analyst Gil Luria aptly observed, you can’t have “stocked more than six months worth of inventory”.

What happens when that inventory depletes? Allow me to paint the grim picture: You’ll need to allow price increases (angering customers), accept lower margins (angering shareholders), or force merchants to accept lower margins (angering the very sellers who make your marketplace valuable). It’s a corporate version of “Pick Your Poison,” except all options lead to the same unpleasant outcome.

The Secret Sauce That Made Amazon… That Nobody Talks About

Let’s discuss something that isn’t in your shareholder letters – the forgotten architect of Amazon’s early success. While everyone credits Jeff’s vision, few remember that Jeff Bezos personally hired a man named Eric Ward to run Amazon’s first link outreach campaign – what people call Amazon Associates, is what SEO’s call backlink outreach campaign on steroids.⁶

This man – who was affectionately and appropriately known as “LinkMoses” in SEO industry circles – built Amazon’s digital infrastructure before digital infrastructure was even a concept. His link-building campaigns regularly achieved 90% success rates in outreach attempts, driving millions of new customers to Amazon when you needed them most.

The great irony is that the internet ecosystem Eric Ward built for Amazon – getting “every blogger and their grandmother to recommend your products” – is precisely what AI shopping assistants will render obsolete. When algorithms make purchasing decisions, all those carefully cultivated product reviews and affiliate links become digital relics.

Bold Prediction From A Digital Archeologist: The future of e-commerce won’t be won through SEO or backlinks or customer reviews. It will be determined by which company writes the most persuasive API documentation for AI shopping assistants.

The Revenge of the Merchants

Remember how Amazon built its empire? By collecting vast amounts of customer and product data while sharing almost none of it with the merchants who actually stock your digital shelves. Those merchants have been forced to pay increasingly steep fees for the privilege of being data-mined and margin-squeezed.

Now, with AI shopping assistants, those same merchants might finally get their revenge. When customers delegate purchases to AI, and those AI agents can shop anywhere, what’s to stop a merchant from creating direct relationships with these AI systems, bypassing Amazon entirely?

As your own “Buy For Me” feature demonstrates, even Amazon recognizes that the walled garden approach has an expiration date. The moment AI shopping assistants become sophisticated enough to handle complex purchasing decisions, the balance of power shifts dramatically away from platforms and toward direct brand relationships.

In Conclusion: The Future Is Here, It’s Just Unevenly Distributed (And Mostly Not In Your Favor)

Andy, I don’t envy your position. You’re steering a supertanker through increasingly treacherous waters. AI shopping assistants are eroding the behavioral economics that drive impulse purchases. Cloud computing is becoming commoditized. Tariffs are forcing impossible choices. Chinese e-commerce competitors like Temu are perfecting their English and their marketing.

The moat that Eric Ward helped build for Amazon – the one that transformed you from a prison filled with books to the promised land of e-commerce – is evaporating in the heat of technological change.⁷ The backlinks that once directed humans to your products will soon be replaced by the APIs and protocols (MCP anyone?) that direct AI agents to the best deals, regardless of platform.

My unsolicited advice? Embrace the chaos. If AI is going to disintermediate everything anyway, be the disintermediator-in-chief. Make Amazon the platform that AI shopping assistants prefer to work with, not because you’ve trapped them, but because you’ve made it advantageous for them.

Or don’t. What do I know? I’m just a columnist who shops at Amazon because it’s marginally more convenient than the alternatives. For now.

Watching with morbid fascination,
Simba, founder of TechOnion.

P.S. If we’re wrong about any of this, please let us know in the comments below. After all, even AI shopping assistants need a good laugh sometimes.

Enjoyed this article? Support independent tech satire! [TechOnion] runs on your donations and the tears of disrupted industry executives. For the price of a Prime membership, you can help us continue peeling back the layers of technological absurdity. Unlike Amazon, we don't have a secret pricing algorithm – give whatever you want, even if it's just thoughts and prayers (though we prefer actual currency).

References

Google Announces ‘Premium Search’: Pay $9.99/Month To Finally See The Internet Again

TechOnion Originals

Simba

-

May 11, 2025

2

Google Announces ‘Premium Search’: Pay $9.99/Month To Finally See The Internet Again

In what company executives are calling “the natural evolution of the search experience,” Google has unveiled its long-rumored Premium Search subscription service, promising users the revolutionary opportunity to occasionally glimpse actual websites amid a sea of targeted advertising. For just $9.99 per month – approximately the cost of three clicks on a “best mattress” Google Ad-subscribers will gain access to a search engine that vaguely resembles the one you used for free back in 2010, which on the internet seems like centuries ago!

The announcement comes as the search giant faces increasing scrutiny over its search result quality, with recent studies showing that only 36% of Google searches now lead users to the open web, while the remainder trap users in Google’s own ecosystem of products, services, and increasingly desperate attempts to monetize your curiosity about whether cats can eat broccoli and enjoy it.

The Premium Search Experience: Like Regular Search But With 17% More Internet

According to the lavish press release issued from Google’s Mountain View headquarters – a document containing precisely 42 instances of the phrase “enhancing user experience” and zero mentions of “revenue extraction” – Premium Search will offer subscribers an array of features previously thought extinct, such as “organic results above-the-fold” and “the ability to find information without first scrolling past seventeen nearly identical products you have no intention of purchasing ever.”

“We’ve heard from our users that they enjoy the thrill of potentially discovering relevant information after engaging with several pages of carefully curated shopping opportunities,” explained Dr. Veronica Matthews, Google’s newly appointed Chief Revenue Persistence Officer. “With Premium Search, we’re streamlining that experience by occasionally showing you what you actually searched for without requiring an archaeology degree.”

Internal documents reportedly reveal that Premium Search will reduce the current standard of 85% ad coverage to a more modest 65%, allowing users to experience what company insiders are calling “nostalgic glimpses of the information superhighway” between promotional content.

The Science of Search Degradation: A Journey of Discovery

The development of Premium Search reportedly began after Google analysts made a startling discovery: reducing search quality had virtually no impact on the company’s market dominance or revenue generation. Despite user complaints about result relevance and ad saturation, Google’s search engine market share remained stubbornly fixed at approximately 90% throughout 2024.

“It was an absolute eureka moment,” said Thomas Rutherford, Google’s SVP of User Tolerance Assessment. “We realized we could gradually decrease the quality-to-advertising ratio by approximately 3.7% per quarter without triggering mass user exodus. The question quickly became not ‘how do we maintain search quality?’ but rather ‘how far can we push this before people notice enough to actually change their search behavior?'”

The answer, it seems, was much further than anyone anticipated. Recent behavioral studies reveal that most Google users now spend 14.6 seconds on average before clicking a result, with 50% clicking within 9 seconds – barely enough time to distinguish between an actual result and a cleverly disguised advertisement.

Even more tellingly, only 9% of users ever make it to the bottom of the first page of results, suggesting that most have either found what they’re looking for or, more likely, have accepted defeat and settled for whatever Google has placed in their path.

The Tiered Subscription Model: Choose Your Own Financial Adventure

Premium Search will launch with three distinct subscription tiers, each offering progressively more access to what was once simply called “search results”:

The “Basic Explorer” tier ($9.99/month) eliminates shopping ads for non-commercial searches and guarantees that at least two organic results will appear above-the-fold – a 200% increase from the current standard.

The “Digital Archaeologist” tier ($19.99/month) reduces total ad load by 40% and introduces the groundbreaking “Result Relevance Guarantee,” which ensures that at least 50% of first-page results will have some tangential relationship to your actual search query.

The flagship “Internet Rememberer” package ($49.99/month) offers the premium experience of “2010 Mode,” recreating the quaint historical period when Google primarily functioned as a tool for finding information rather than a sophisticated shopping mall with occasional factual content.

“We’re particularly excited about the Internet Rememberer tier,” explained Jennifer Blackwood, Google’s Director of Nostalgia Monetization. “Our research shows that users over 30 have powerful emotional connections to the concept of ‘finding things on the internet,’ and we’ve developed a way to leverage that nostalgia into an optimized revenue stream.”

The AI Justification: Computing Power Doesn’t Grow on Trees (Except in Our Carbon Offset Programs)

Google executives have justified the subscription model by pointing to the computational costs of their advanced AI systems, particularly the Search Generative Experience (SGE) and the recently launched AI Mode.

“Generating AI responses requires significant computational resources,” explained Dr. Harold Fitzwilliam, Google’s Director of Financial Explanation Creation. “For example, when you ask a complex query like ‘What’s the difference between sleep tracking on smart rings versus smartwatches?’ our systems must analyze billions of data points, consult multiple sources, and craft a comprehensive response that saves you the trouble of visiting any of the websites that actually created that information.”

What Dr. Fitzwilliam failed to mention was that Google generated $175 billion in search-related ad revenue last year alone, a sum that could theoretically power the entire computational needs of SGE while leaving enough surplus to end world hunger, solve climate change, and still fund a modest space program.

When pressed on this point at the announcement event, Google CEO Sundar Pichai reportedly stared blankly for 9.3 seconds before responding, “The future of search is a journey we’re taking together with our users and advertisers,” a statement that received thunderous applause despite containing no actual information.

The True Cost of Free: Your Data, Your Soul, and Now Your Credit Card

Perhaps the most remarkable aspect of Premium Search is its adherence to Google’s core business model: even paying subscribers will still see ads. The $9.99 monthly fee merely reduces their volume and adjusts their prominence, creating what one anonymous Google engineer described as “the illusion of escape from our advertising ecosystem.”

“It’s really quite brilliant,” explained digital economist Dr. Victoria Chang. “Google has created a problem – the oversaturation of search results with ads – and is now charging users to partially solve that same problem. It’s like charging people to use slightly less uncomfortable airplane seats after systematically making all airplane seats uncomfortable.”

This strategy aligns perfectly with internal research showing that humans will pay substantial sums to temporarily alleviate artificially created discomfort. The same research indicated that 73% of users who complained about Google’s ad-heavy results would still prefer paying Google to fix the problem rather than switching to an alternative search engine.

“Our user surveys show a fascinating psychological phenomenon,” noted Dr. Marcus Wellington, Google’s Chief Behavioral Economist. “Even when presented with free alternatives, users express a preference for paying to continue using the degraded service they’ve grown accustomed to. We call this the ‘Stockholm Search Syndrome.'”

The Curious Case of the Search Engine That Stopped Searching

The most overlooked aspect of Premium Search may be what it reveals about Google’s long-term strategy. By charging for a slightly less advertising-dominated experience, Google effectively acknowledges what critics have long suspected: the company’s primary purpose is no longer organizing the world’s information but rather monetizing access to it.

This represents the culmination of a gradual transformation that began years ago. What started as a simple, elegant tool for navigating the internet has evolved into an elaborate system for guiding users toward commercial transactions while extracting maximum value from their attention.

“The search engine’s purpose was originally to help you find things on the internet,” explained digital historian Eleanor Abernathy. “But somewhere along the way, that purpose shifted. Now its primary function is to help ads find you, with actual information discovery as a secondary or even tertiary concern.”

This shift is reflected in the user experience. Today, a typical Google search presents users with a complex obstacle course of Ai answers, ads, shopping results, featured snippets, and various SERP features before they can reach an actual website. Premium Search doesn’t eliminate this obstacle course – it merely removes a few of the more obvious hurdles.

The Future of Premium Search: Your Grandchildren Will Never Believe Search Was Once Free

Industry analysts predict that Premium Search represents just the first step in a broader strategy to monetize previously free aspects of Google’s services. Internal documents allegedly outline plans for additional premium tiers, including:

“Premium Gmail” ($7.99/month): Reduces the number of sponsored emails and guarantees delivery of important messages to your actual inbox rather than promotions or spam.

“Premium Maps” ($6.99/month): Shows routes that aren’t deliberately designed to pass sponsored businesses.

“Premium Android” ($14.99/month): Disables features that were intentionally designed to be confusing or frustrating unless you pay to fix them.

The most ambitious plan, however, appears to be “Premium Internet” ($99.99/month), which would theoretically allow users to experience the internet as it existed before it was optimized for engagement metrics and advertising revenue.

When asked about these rumored services, a Google spokesperson replied, “While we can’t comment on future products, we’re always exploring ways to enhance the user experience through innovative monetization strategies that create value for our advertising partners while maintaining the illusion of user agency.”

The Search Resistance: A Small But Growing Movement

Not everyone is embracing Google’s new premium model. A small but growing segment of users has begun migrating to alternative AI search platforms like Perplexity, which saw a 47% increase in traffic following Google’s announcement.

“I finally reached my breaking point when I searched for ‘symptoms of appendicitis’ and had to scroll past four ads for appendix-shaped throw pillows before I could find medical information,” explained former Google user Sam Mitchell. “By that point, my appendix had actually ruptured, which I suppose is the ultimate bounce-back to the search results page.”

Meanwhile, digital rights advocate Jennifer Patel has organized what she calls the “Search Liberation Front,” a movement dedicated to helping users break their Google dependency. “We run support groups where people learn to perform basic tasks like finding a recipe without first being shown 17 different Air Fryers they could purchase,” she explained. “The withdrawal symptoms can be severe – one man experienced panic attacks when he realized DuckDuckGo doesn’t know his location within three feet at all times.”

Whether these resistance efforts will impact Google’s dominant market position remains to be seen. As one analyst noted, “Google has achieved what economists once thought impossible: they’ve made their service progressively worse while simultaneously increasing both user numbers and revenue. It’s like a restaurant making their food gradually more expensive and less tasty, yet somehow attracting more customers who are willing to pay extra for slightly less terrible meals.”

Have you already received your Premium Search invitation, or are you still stuck with the peasant version where you have to scroll past seventeen shopping ads before you can learn if that rash is serious? Will you be shelling out $9.99 a month to slightly reduce the commercial content in your search results, or have you already joined the search engine resistance? Share your search horror stories or premium experiences in the comments below!

Support TechOnion

If you enjoyed this article and want to support independent tech journalism that doesn't literally charge you to read fewer ads, consider donating to TechOnion. For just $8.99/month (that's $1 less than Google Premium Search!), you can fund our ongoing investigation into whether the internet is actually still there beneath all the advertisements. Your contribution helps ensure we can continue to peel back the layers of tech absurdity without first showing you fourteen different types of vegetable peelers you might want to purchase. Remember: in a world where even Google is charging you to see slightly fewer ads, TechOnion remains committed to showing you exactly zero shopping recommendations for products tangentially related to onions.

The iFold Cometh: Apple Reinvents the Wheel While Steve Jobs Performs 10,000 RPM in His Titanium Mausoleum

Gadgets

Simba

-

May 11, 2025

1

The iFold Cometh: Apple Reinvents the Wheel While Steve Jobs Performs 10,000 RPM in His Titanium Mausoleum

In a shocking twist that absolutely no one saw coming except literally everyone with a passing interest in consumer technology, Apple plans to release its revolutionary, groundbreaking, paradigm-shifting foldable iPhone in 2026. The device, which industry insiders definitely aren’t calling the “iFold” because that would require Apple’s naming department to experience a genuine creative impulse, will arrive a mere seven years after Samsung first introduced the concept to the market. At this pace, we can expect Apple to invent teleportation approximately 45 years after everyone else has been beaming to work.

According to multiple reports that Apple has neither confirmed nor deployed black-ops teams to suppress, the foldable iPhone will feature a book-style design with a 5.7-inch outer display when closed and an approximately 8-inch screen when unfolded.¹ This marks the first time in history Apple has looked at Samsung’s homework, waited half a decade, and then turned in the same assignment with slightly supposed better handwriting.

Tim Cook’s Grand Vision: Make Products Thinner Until They Literally Disappear

The foldable iPhone will reportedly measure between 4.5mm and 4.8mm when unfolded, continuing Apple’s relentless pursuit of devices so thin they can only be seen when viewed edge-on.² Apple engineers have apparently solved the problem of “physics” and “material strength” by creating a device that, when measured by conventional instruments, technically has negative thickness.

“Our revolutionary foldable has the structural integrity of tissue paper but costs as much as a used car,” said a Apple executive while rhythmically tapping on a MacBook made of recycled aluminum and the tears of repair technicians. “We’ve invested billions in creating a hinge so sophisticated that it will absolutely, positively not break unless you look at it wrong, breathe near it, or attempt to use it for its intended purpose.”

Industry analysts speculate that the device will incorporate titanium and stainless steel in its hinge mechanism, presumably so that when it inevitably breaks, you can melt it down and recover at least $15 worth of precious metals from your $2,500 investment.³

Apple’s Bold New Pricing Strategy: “What If We Just Charged More?”

Speaking of that price tag, multiple reports suggest the foldable iPhone will retail between $2,000 and $2,500, making it the most expensive iPhone ever and cementing Apple’s position as the only company that can convince consumers that paying mortgage-level prices for a phone is perfectly reasonable.⁴

“Our market research indicates that many Apple customers still have functioning kidneys, which represents an untapped revenue stream,” explained a Apple CFO while bathing in a tub of liquid cash. “The $2,500 price point was carefully calculated based on the maximum amount we can charge before people start questioning their life choices, multiplied by the blind Apple brand loyalty coefficient.”

When asked why the foldable would cost more than twice as much as the standard iPhone, the executive smiled knowingly. “We’ve added a hinge. Do you have any idea how expensive hinges are? They’re practically extinct in the wild. We had to breed them in captivity.”

The Launch Schedule Shuffle: “It’s Not Confusing If You’re Rich Enough”

In what tech journalists are describing as “a spreadsheet nightmare,” Apple plans to completely revamp its iPhone launch strategy to accommodate the foldable device. Starting in 2026, the company will release the iPhone 18 Pro models, a mysterious “Air” variant, and the foldable in fall 2026, while delaying the standard iPhone 18 until spring 2027.

This staggered release schedule – which would require an advanced degree in Apple Product Management to comprehend – is reportedly designed to “streamline” the broader six-model iPhone lineup.⁵ Because nothing says “streamlined” like splitting your flagship product launch across two separate seasons of the year.

“We found that having a single, easy-to-understand product launch each year was causing dangerous levels of customer satisfaction,” said a Apple marketing director. “Our new approach ensures that no matter when you buy an iPhone, you can immediately experience the crushing regret of knowing a better one is coming out in six months.”

The company’s internal research apparently shows that customer confusion leads to panic buying of the most expensive model available, in a psychological phenomenon economists call “just make it stop pricing.”

The Face ID Vanishing Act: “We Put It Under the Display Because We Can”

In addition to folding innovations, the 2026 iPhone Pro models will reportedly feature under-display Face ID technology, with the facial recognition hardware embedded beneath the screen. This breakthrough allows Apple to shrink the Dynamic Island cutout to a small pill or hole in the top-left corner, in what engineers are calling “Dynamic Peninsula” or possibly “Dynamic Archipelago” depending on which marketing focus group responds better.

“We’ve managed to hide the Face ID sensors under the display,” boasted a conjectural Apple engineer. “Not because anyone asked for it or because it meaningfully improves the user experience, but because Samsung did it and we needed something else to mention in the keynote besides the fold.”

When questioned about potential reliability issues with the hidden sensors, the engineer nodded thoughtfully. “Oh, they’ll absolutely be less reliable. But they’ll be less reliable elegantly.”

The Courage to Follow: Apple’s Bold New Direction of Going Where Others Have Been

Perhaps the most remarkable aspect of Apple’s foldable plans is the company’s breathtaking courage to follow in the footsteps of nearly every other major smartphone manufacturer. After watching Samsung, Motorola, Google, and various Chinese companies pioneer and refine foldable technology since 2019, Apple has finally decided the concept is sufficiently mature to receive the blessing of its marketing department.⁶

“We believe foldables represent the future of smartphones,” declared an apocryphal Apple VP of Innovation while adjusting his perfectly circular glasses. “Not the past future, which was five years ago when everyone else released them, but the future future, which is when we decide to acknowledge their existence.”

When reminded that Samsung is already on its sixth generation of foldable phones, the executive smiled thinly. “Yes, but have they charged $2,500 for one and called it ‘magical’? Checkmate!”

The iPad Division’s Existential Crisis: “We’re In Danger, Aren’t We?”

The most fascinating aspect of this development is Apple’s apparent willingness to cannibalize iPad sales, breaking with its historical approach of maintaining clear boundaries between product categories.

“For years, Apple told us touchscreen Macs would never happen because they would hurt iPad sales,” explained industry analyst Victoria Richards. “Now they are making a phone that unfolds into an iPad. It’s like watching a strict vegetarian order a 40-ounce ribeye while explaining they have always been a carnivore.”

The iPad division is reportedly in a collective state of panic. “I just got people to start using this thing for actual work instead of just watching Netflix in bed,” lamented an iPad product manager into their locally-sourced kombucha. “Now they’re going to fold a phone in half and call it an iPad killer? I should have taken that job at Microsoft.”

When asked about the potential impact on iPad sales, an Apple executive deflected. “The iFold – I mean, the foldable iPhone – creates an entirely new product category. It’s not a phone. It’s not a tablet. It’s a… phablet. Wait, no, Samsung used that name. It’s a… foldy-phone-pad-thing. Our marketing department is still workshopping it.”

The $700 Million Crease Solution: “It’s Not a Crease, It’s a Feature”

One area where Apple genuinely appears to be innovating is in solving the dreaded “crease problem” that has plagued foldable displays. Reports indicate that Apple’s foldable will feature a display that appears crease-free to the human eye, thanks to a development effort that likely cost more than the GDP of Mauritius.

“We’ve spent approximately $700 million eliminating the crease,” bragged an Apple materials scientist. “Not because it affected functionality in any meaningful way, but because it offended Jony Ive’s ghost, which still haunts our design studio despite him having left the company years ago and being very much alive.”

The solution reportedly involves a proprietary combination of ultra-thin glass, nanopolymers, and the tears of Android users who paid $1,800 for first-generation foldables that broke within a week.

The 20th Anniversary Gift: A Completely Different Philosophy

In what can only be described as cosmic timing, Apple’s second-generation foldable is set to launch in 2027 – exactly twenty years after Jobs unveiled the original iPhone. This perfect symmetry suggests either brilliant marketing or that Tim Cook has discovered time travel.

“For the 20th anniversary of the product that changed everything, we wanted to create something special,” an Apple executive might say. “So we decided to completely abandon its foundational principles and make it fold in half. It’s poetic, really.”

The irony isn’t lost on tech historians who recall Jobs’ original iPhone presentation, where he mocked other phones for having too many buttons and moving parts. Two decades later, Apple’s solution appears to be adding the most significant moving part possible: a massive hinge that transforms their sleek monolith into what is essentially two phones stuck together with industrial-strength tape.

“Steve always said the consumer doesn’t know what they want until we show it to them,” said Tim Cook’s evil twin, Jim Cook. “We’ve updated that to: The consumer doesn’t know what they want until Samsung shows it to them, they buy it, and then we make a slightly more polished version five years later and charge double.”

What do you think? Will you be mortgaging your home to purchase the Apple iFold when it arrives in 2026? Will Steve Jobs complete his transformation into a perpetual motion machine? Has Apple finally run out of ideas, or is this genuinely the next evolution of the smartphone? Comment below with your hottest takes on Apple’s bendable future.

And if this article gave you a chuckle, consider donating to TechOnion-we need the funds to develop a foldable newsletter that's thinner, lighter, and three times more expensive than reading it on your phone.

References

The Upside-Down Revolution: How Apple’s Magic Mouse Charging Port Creates Character While Destroying Productivity

Gadgets

Simba

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May 11, 2025

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The Upside-Down Revolution: How Apple’s Magic Mouse Charging Port Creates Character While Destroying Productivity

In what tech historians are calling “the most deliberate inconvenience since the invention of automatic phone menus,” Apple has once again released a Magic Mouse with its charging port stubbornly located on the bottom, rendering the device completely unusable during charging. The latest USB-C version of the Magic Mouse, released in October 2024, continues Apple’s brave tradition of forcing users to flip their mice belly-up like exhausted turtles whenever battery life dwindles.¹

This design choice – which has persisted through multiple iterations and almost a decade of mockery – stands as perhaps the most perfect metaphor for Apple’s relationship with its customers: beautiful, expensive, innovative, and absolutely infuriating in ways that make you question whether the company secretly hates its customers.

The Charging Position: Technically Called “Dead Bug Mode”

When plugged in, the Magic Mouse must be flipped on its back, with its smooth white surface facing upward and the charging cable protruding from its underside like a technological umbilical cord. This position has been affectionately dubbed “dead bug mode” by users, who note the similarity to an insect that has reached the end of its lifecycle and accepted its fate.²

“It’s actually quite elegant when you think about it,” explained an Apple design executive while carefully polishing what appeared to be a solid gold paperweight. “Most companies would allow a mouse to be used while charging, forcing users to continue working. We’ve created a mandatory two-minute meditation break. Your mouse isn’t broken – it’s teaching you mindfulness.”

According to internal documents that definitely exist, Apple has categorized this feature under “Enforced Digital Wellbeing” in its design philosophy handbook, alongside other wellness initiatives such as “Battery Anxiety as Cardiac Exercise” and “Face ID Failures as Momentary Zen Koans.”

Steve Jobs Would Have Loved It (Or Fired Everyone Involved)

Despite popular memes suggesting Steve Jobs would “never have let this happen,” Apple insiders insist that Jobs would have embraced the upside-down charging design as a character-building exercise for users.³

“Steve always believed technology should have personality,” said a former Jobs associate who requested anonymity because they fear being mocked in an Aaron Sorkin screenplay. “And what builds more character than feeling slightly inconvenienced several times a month? Steve used to say that true innovation happens in moments of frustration, usually around 3 AM when you’re trying to finish a project and your magic mouse dies.”

This perspective contradicts well-documented evidence that Jobs was fanatical about usability and once fired an engineer for a rounded corner when he wanted a square one. However, Jobs was also known for his strong opinions about mouse design, famously resisting multi-button mice until late in his tenure.⁴

“Steve was a firm believer in the fact that if you make the user interface (UI) good enough, you should be able to do everything you need with just one button,” said Abraham Farag, Apple’s former Senior Mechanical Engineer of Product Design. This single-button philosophy eventually evolved into the Magic Mouse’s touch-sensitive surface – a design compromise that allowed for right-click functionality without visible buttons.

When asked if Jobs would have approved of a mouse that becomes completely useless while charging, the Apple executive smiled knowingly. “Steve used to say, ‘The best interface is no interface.’ We’ve just taken that to its logical conclusion – sometimes the best mouse is no mouse at all.”

The Secret Origin Story: A Design Choice Born of Necessity (or Laziness)

According to product designers who have analyzed the Magic Mouse, the controversial charging port location wasn’t originally intended as a philosophical statement about mindfulness or character-building, but rather stemmed from practical considerations during the transition from the battery-powered Magic Mouse 1 to the rechargeable Magic Mouse 2.⁵

“The first Magic Mouse had removable batteries and wasn’t charged with a cable,” explained a product designer on Reddit. “When Apple made the Magic Keyboard 2 with non-removable batteries, it was also time for the Magic Mouse to get rid of the batteries… But Apple is known for not changing the whole design if it’s not really necessary!”⁶

This explanation suggests the bottom placement was merely the path of least resistance – the batteries were already located on the bottom of the original Magic Mouse, so Apple simply replaced them with a rechargeable battery and added a charging port in the same location.

However, this pragmatic explanation fails to account for Apple’s decision to maintain this design for almost a decade, across multiple product refreshes, despite widespread mockery and the obvious solution of moving the port to the front of the device.

The Two-Minute Defense: “It Charges Really Fast, Though”

Apple defenders (also known as “people who have spent too much on Apple products to admit any disappointment”) frequently point to the Magic Mouse’s quick charging capabilities as justification for its upside-down design quirk.

“It takes 2 minutes to get more than a full day’s charge,” noted one Reddit user, suggesting the inconvenience is minimal. Apple’s promotional materials claim that just two minutes of charging will provide nine hours of use, theoretically allowing users to plug in during a coffee break and return to a mouse that will last the rest of the workday.

This defense, while technically accurate, fails to address the fundamental question: Why not just put the charging port on the front so people can keep working while charging???

“The answer is obvious,” insisted our Apple executive. “If we put the charging port on the front, users would leave it plugged in all the time, transforming our beautiful, sleek, wireless mouse into a wired one. That’s like buying a Ferrari and then attaching a trailer hitch. It undermines the entire aesthetic experience.”

The Cult of Inconvenience: Apple’s Secret Design Philosophy

To understand Apple’s commitment to the upside-down charging port, one must understand a secret design philosophy that has allegedly guided the company since its earliest days: “Curated Inconvenience Theory.”

According to this completely plausible theory, Apple deliberately introduces small frustrations into its products to create a sense of shared struggle among Apple users, fostering brand loyalty through a phenomenon similar to Stockholm syndrome.

“It’s like hazing for a fraternity,” explained Dr. Eleanor Rigby, Professor of Consumer Psychology at a prestigious university that definitely exists. “These small inconveniences – dongles, proprietary cables, charging ports in ridiculous locations – create a sense of belonging. When you see another person flipping their Magic Mouse upside down in a coffee shop, you share a knowing glance. You’re both members of the same exclusive club of people who have chosen to be mildly inconvenienced for aesthetic reasons.”

This theory explains other Apple design choices, from removing headphone jacks to the brief disaster of the butterfly keyboard. They’re not bugs; they’re features designed to strengthen user loyalty through shared suffering.

The 2024 Update: Same Ridiculousness, New Port

In October 2024, when Apple finally updated the Magic Mouse with USB-C to match the rest of its product line, many hoped the company would take the opportunity to relocate the charging port to a more sensible position. Those hopes were dashed when images revealed the new Magic Mouse maintained the same upside-down charging design, just with a different port shape.

“Although it now has USB-C, the charging port is still on the bottom of the mouse,” reported 9to5Mac, in what might be the least surprising tech news of 2024.

This steadfast commitment to an objectively terrible design choice has left even the most dedicated Apple fans questioning whether the company is simply trolling its user base at this point.

“Priced at $99, this latest Magic Mouse indicates that Apple still believes the most effective method for charging the device is to flip it upside down, rendering it unusable during the charging process,” The Verge reported, with what one imagines was a heavy sigh.

The Future of Magic Mouse Design: “It Gets Worse”

According to sources close to Apple’s design, the company has even more inconvenient charging solutions planned for future Magic Mouse iterations.

“We’re looking at several exciting new charging mechanisms,” revealed a Apple innovation lead. “One prototype requires users to balance the mouse on its side like a coin. Another must be submerged in a proprietary charging fluid that costs $49.99 per ounce. My personal favorite requires users to gently stroke the mouse while whispering affirmations to it.”

When asked why the company doesn’t simply move the port to the front like literally every other rechargeable mouse on the market, the innovation lead stared blankly for several seconds before responding: “I don’t understand the question.”

The Deeper Meaning: An Existential Crisis Disguised as a Mouse

Perhaps the Magic Mouse’s upside-down charging design isn’t just about aesthetics or tradition or even stubbornness. Perhaps it’s a profound statement about the nature of technology itself – sometimes beautiful, sometimes useful, but never quite perfect.

In a world where we expect our devices to be flawless extensions of ourselves, the Magic Mouse stands as a reminder of our own limitations. Like us, it occasionally needs to rest, to recharge, to take a break from constant productivity.

Or maybe, just maybe, it’s a terrible design that Apple is too proud to fix.

As the Magic Mouse lies helplessly on its back, charging cable protruding awkwardly from its smooth underbelly, it serves as the perfect metaphor for our relationship with technology: elegant, powerful, expensive, and occasionally infuriating in ways that make you question everything about your life choices.

What do you think? Is the Magic Mouse’s upside-down charging port a stroke of design genius or the most irritating example of form over function in modern tech? Have you ever lost critical work time because your mouse was lying helplessly on its back like an overturned tortoise? Share your Magic Mouse horror stories in the comments below. 💝🎁

And if this article made you chuckle while simultaneously questioning your expensive tech purchases, consider donating to TechOnion-we accept all forms of payment except Magic Mice that are currently charging.

References

DOGE Capital: Elon Musk’s Ultimate Startup Where MVP Stands for ‘Minimum Viable Presidency’

Tech

Simba

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May 11, 2025

0

DOGE Capital: Elon Musk’s Ultimate Startup Where MVP Stands for ‘Minimum Viable Presidency’

In the gleaming corridors of what used to be the U.S. Digital Services – now rebranded as the U.S. DOGE Service – a revolution is unfolding. Elon Musk, the man who promised to colonize Mars, revolutionize transportation, and implant chips in human brains, has now set his sights on a truly impossible challenge: making the U.S. government efficient.

The Department of Government Efficiency (DOGE), despite not being an official government department (because only Congress can create those, but why let constitutional details get in the way of disruption?), has become Musk’s latest venture.¹ And like any good Silicon Valley founder, he’s applying the same proven strategy that has worked for all his companies: setting impossible goals, demanding employees work like they’re possessed, sending bizarre late-night communications, and leaving just before the consequences arrive.²

The Lean Government Canvas

Musk’s approach to government transformation follows the classic lean startup methodology. First, identify a problem: government inefficiency. Second, propose a solution so audacious it sounds made up: cut $1-2 trillion from federal spending.³ Third, build a Minimum Viable Product: in this case, a Minimum Viable Presidency where essential services like Social Security and Medicare are treated as optional features that can be cut from the sprint if they don’t show immediate ROI.⁴

“We need to run the government like we run SpaceX,” Musk reportedly told a room full of civil servants with 30-year careers in public administration. “When code doesn’t work, we delete it. When a rocket explodes, we build another one. When employees complain about bathroom breaks, we remind them that Mars isn’t colonizing itself.”

The bewildered federal employees nodded, wondering if their healthcare benefits could survive a rapid iteration cycle.

Pivoting the Constitution

One of DOGE’s most innovative strategies has been its willingness to “pivot” away from constitutional constraints. When faced with the reality that only the US Congress can create departments or appropriate funds, the DOGE team simply reframed the limitation as “legacy thinking” that needed disruption.⁵

“The Constitution is basically just version 1.0 of the government’s operating system,” explained a DOGE spokesperson who previously worked at three failed NFT marketplaces. “It was written when people used quills. We use Slack now. Evolution is inevitable.”

This approach has led to several “growth hacks,” such as demanding all federal employees justify their existence in five bullet points or face automatic “user churn” (previously known as “firing”), attempting to access and modify sensitive Treasury payment systems (dismissed as “just playing around in the sandbox”), and declaring entire agencies redundant after a 12-minute evaluation (described as “efficient decision velocity”).⁶

The Crazy Uncle Economy

Inside sources report that many in the Trump administration have taken to calling Elon Musk “Crazy Uncle Elon,” a nickname that captures both his penchant for dad jokes and his resemblance to that relative who corners you at Thanksgiving to explain his theory about how the microwave is spying on him.

“I’ve shared a room with Elon Musk, and he constantly attempts to be humorous,” a senior Trump administration official told Rolling Stone. “And he simply isn’t funny. Not even close.”

This communication style has permeated DOGE’s operations. Federal agencies now receive policy directives interspersed with memes, references to ’69,’ and occasional graphic sexual images sent to federal employees. When one department head questioned whether this was appropriate government communication, they reportedly received a response consisting solely of the ‘Deal With It’ sunglasses GIF.

The East India Company 2.0 has arrived, and it communicates exclusively in impact font.

The Data-Driven Government (Your Data, His Government)

Perhaps the most concerning aspect of DOGE’s operation is its unprecedented access to sensitive government systems. Reports indicate DOGE employees have obtained permission to view data in the U.S. government’s payment system, which includes bank account information, Social Security numbers, and income tax documents.

This has led to what Musk calls “data-driven governance.” In startup parlance, this means making decisions based on metrics and analytics. In practical terms, it means a Tesla engineer with no government experience now potentially has access to your tax returns.

“This is just standard A/B testing,” Musk explained when questioned about reports that DOGE was experimenting with blocking certain government payments. “We’re seeing what happens if we just don’t send Social Security checks to, say, every third person. Does it really impact quality of life metrics? The data will tell us.”

When reminded that these “metrics” represent actual human beings depending on those payments, Musk reportedly became defensive. “Look, every great product requires user sacrifice. You think the first Tesla didn’t catch fire sometimes? Excellence requires iteration.”

The Conflict of Interest Economy

The most remarkable achievement of DOGE may be its ability to transform potential conflicts of interest into what Musk calls “vertical integration opportunities.”

Consider that Musk controls companies with billions in federal contracts, including SpaceX, Tesla, The Boring Company, Neuralink, and xAI, and now has direct access to the inner workings of the very agencies that oversee and pay for those contracts.

In any previous administration, this might have raised ethical concerns. In the DOGE era, it’s simply described as “eliminating inefficient middlemen” and “streamlining the value chain.”

“It just makes sense,” explained a DOGE team member wearing a ‘HODL Government’ t-shirt. “Why should Elon have to wait for some bureaucrat to approve a SpaceX payment when he can just approve it himself? That cuts out like, three weeks of paperwork.”

The Hackathon Governance Model

One of DOGE’s signature innovations is the introduction of “hackathons” to solve intractable government problems. These events bring together Silicon Valley technologists to spend a weekend developing solutions to complex issues that career public servants have spent decades addressing.⁷

“We had this amazing hackathon to solve the Social Security processing backlog,” enthused a DOGE product manager. “These incredible developers who’ve never worked in benefits administration spent 48 hours fueled by Red Bull and came up with an app that lets seniors rate their caseworkers with emoji. Disruption complete!”

When asked whether the app addressed the fundamental funding and staffing issues plaguing Social Security, the product manager appeared confused. “No, no, you don’t understand startup methodology. First, you build something simple that doesn’t work very well but has good user experience (UX). Then you raise more money based on user growth. The actual functionality comes in version 3.0, after you’ve achieved unicorn status.”

The seniors, meanwhile, continue waiting for their benefits.

The Minimum Viable Democracy

As Musk’s 130-day cap on government work approaches, questions remain about what lasting impact DOGE will have. Will it truly transform government, or will it join the long list of Musk projects that began with bold promises but faced significant delays and scaled-back expectations?

“I think what most people don’t understand is that democracy itself is just another product,” explained a venture capitalist who serves as an unofficial DOGE advisor. “And like any product, you need to focus on your power users – in this case, billionaires and corporations – while paying just enough attention to the free-tier users – regular US citizens – to maintain growth metrics.”

When asked what metrics DOGE uses to measure success, the advisor shrugged. “The usual: reduced headcount, increased founder control, and a valuation that bears no relationship to actual performance. Standard unicorn stuff.”

The Exit Strategy

As with any startup founder, Musk appears to have a carefully planned exit strategy. Recent announcements indicate he will reduce his DOGE commitment to “just one or two days per week” starting in May, just as legal challenges mount and the practical difficulties of government transformation become apparent.

This follows the classic Silicon Valley pattern: make grandiose promises, attract massive attention, encounter difficult realities, then gradually distance yourself while maintaining enough connection to claim credit for any successes while avoiding blame for failures.

“Elon is a visionary,” explained a DOGE spokesperson. “His job is to see the future and point at it, not necessarily to build the actual road that gets us there. That’s for the operations team.”

When asked who comprises this operations team, the spokesperson gestured vaguely at the depleted federal workforce, many of whom were currently updating their LinkedIn profiles.

The Blockchain Government

Among DOGE’s most ambitious proposals is putting “everything on the blockchain” to ensure transparency. This initiative promises to make government spending data public and tamper-proof – a noble goal that somehow neglects to address how this technology would work with existing federal systems, many of which still run on COBOL.

“We’re going to NFT the entire federal budget,” declared a DOGE blockchain evangelist who previously worked on seven discontinued cryptocurrency projects. “Each department will be a token, and citizens can vote on funding allocations with their governance tokens. It’s direct democracy plus DeFi. Revolutionary!”

When asked how elderly Americans without crypto wallets would participate in this system, the evangelist appeared momentarily stumped before brightening. “That’s what’s so genius about it – if you can’t figure out how to set up a wallet, you probably shouldn’t be voting on fiscal policy anyway. Self-selecting user base!”

The ‘Yes Minister’ Reality

The DOGE experiment has drawn comparisons to the British satirical series “Yes Minister,” where bureaucracy isn’t just a system, but a labyrinth engineered to perpetuate itself. In the show, civil servants expertly stonewall any attempt at change, wielding obscure regulations and jargon as weapons.

Now Musk, like the fictional Jim Hacker, finds himself promising revolutionary change while confronting a government machine that has perfected the art of inertia. The difference is that Musk doesn’t have a Sir Humphrey Appleby to explain why his ideas won’t work – he simply fires anyone who tries.

“The civil service doesn’t resist change because it’s inefficient,” explained a former government efficiency expert. “It resists change because stability is its product. Musk is treating a nuclear power plant like it’s a mobile app – you can’t just turn it off and on again without consequences.”

The Real DOGE Revolution

Perhaps the most profound insight revealed by the DOGE experiment isn’t about government efficiency at all. It’s about the growing convergence of corporate and government power in the hands of a tech elite who view democratic governance as just another legacy system ripe for disruption.

In 1600, the British East India Company began as a trading firm before gradually acquiring quasi-governmental powers and ultimately ruling over colonies. Today, we’re witnessing a similar pattern, but at digital speed. The Department of Government Efficiency represents not just an attempt to streamline bureaucracy but a fundamental rethinking of who government serves and who should control it.

As DOGE continues its mission to “eliminate the tyranny of bureaucracy,” one can’t help but wonder if we’re simply exchanging one form of tyranny for another – replacing slow-moving, accountable public institutions with the whims of billionaires who move fast, break things, and answer to no one.

But hey, at least the memes are dank!

Have thoughts on Musk’s government efficiency revolution? Do you think running government like a startup is the future or a Silicon Valley fever dream? Has DOGE actually accomplished anything besides generating headlines and lawsuits? Share your take in the comments below – but keep it under 280 characters, or Crazy Uncle Elon might not read it.

If you enjoyed this analysis of our new techno-feudal future, consider supporting TechOnion with a donation. For just the price of one government hackathon Red Bull, you can help us continue peeling back the layers of absurdity as billionaires transform democracy into their personal side projects. Think of it as your hedge against becoming an unpaid beta tester in Government 2.0.

References

The Leather Jacket Prophecies: An Open Letter to Jensen Huang Before Nvidia’s $3 Trillion Empire Crumbles Under the Weight of Its Own GPUs

TechOnion Originals

Simba

-

May 8, 2025

0

The Leather Jacket Prophecies: An Open Letter to Jensen Huang Before Nvidia’s $3 Trillion Empire Crumbles Under the Weight of Its Own GPUs

Dear Jensen Huang,

First, congratulations on propelling Nvidia to a $3+ trillion market cap. You’ve managed to convince the world that a company selling glorified math processors should be valued higher than entire African nation-states. As you ponder your next world-changing keynote from atop your throne of melted graphics cards, we thought we would offer some unsolicited and most likely unwelcome advice before your empire of silicon and leather jackets faces the inevitable cooling phase.

Remember When You Actually Made Things for Gamers?

Jensen, it feels like just yesterday you were a plucky entrepreneur launching Nvidia from a Denny’s booth, surviving only on pancakes and determination. Now you are the 18th wealthiest person in the world with a net worth of $100.2 billion, and it seems you’ve developed a peculiar form of corporate amnesia.¹

Let me remind you: before you became AI’s favorite leather-clad prophet, Nvidia made GPUs for gamers. You know, those strange creatures who paid over-the-top prices to render virtual dragons at increasingly ridiculous frame rates? The ones who built your company before “artificial intelligence” became the corporate equivalent of adding “blockchain” to a company name in 2017?

Your invention of the GPU in 1999 sparked the growth of the PC gaming market.² Yet at your CES 2025 keynote, you barely mentioned gaming before pivoting to self-driving cars, humanoid robots, and Project DIGITS.³ Even when you announced the GeForce RTX 50-series, it felt like an obligatory nod to your past – like a rockstar reluctantly playing their old hit song before launching into the experimental jazz-amapiano fusion album nobody asked for.

Remember Amazon’s core mission? They started with books but never abandoned retail while building AWS. Your core audience still consists of gamers who need to render polygons at ludicrous speeds to feel alive. Don’t leave them behind while you’re busy torturing employees into greatness.⁴

The AI Bubble Bath: Soaking in Hype Until Your Fingers Prune

The world is experiencing an unprecedented case of collective AI amnesia. Everyone seems to have forgotten that neural networks have existed since the 1950s, and that we have cycled through AI winters and springs more regularly than fashion trends.

In March 2024, you were compared to Taylor Swift by none other than Mark Zuckerberg. Is that not the clearest sign of a bubble? When tech CEOs start having the cultural impact of pop stars, it’s time to check your tech stocks portfolio diversification.

You have masterfully positioned Nvidia as the shovel-seller in the AI gold rush. But Jensen, what happens when miners realize the gold might be pyrite? You are betting everything on the belief that companies will continue dumping billions into AI infrastructure without demanding clear returns (ROI). You’ve gone from “our company is thirty days from going out of business” to “AI needs 100 times more computation than we thought last year”.⁵ Convenient, isn’t it?

Your recent declaration that “almost the entire world got it wrong” about AI computation needs is either brilliant foresight or the most elegant corporate upsell in history. “Sorry folks, turns out you need 1,000x more of our products than we initially said! Total coincidence that we happen to be the only company selling them – ooops!”

Geopolitical Fence-Sitting: The US-China AI Split and Your $50 Billion Dilemma

Jensen, you are attempting the most precarious balancing act since Philippe Petit walked between the Twin Towers. On one hand, you are telling American policymakers that the US must “embrace AI technology” and “invest in reskilling” – this sounds patriotic enough.⁶ On the other ai robotic hand of yours, you are lamenting to investors that losing access to China’s “$50 billion” AI market would be a “tremendous loss”.⁷

You’ve already disclosed a $5.5 billion hit to earnings due to restrictions on sales of H20 chips to China. Yet simultaneously, you are collaborating with Foxconn to assemble AI servers near Houston, earning praise from President Trump who now conveniently calls you “my friend Jensen”.⁸

Meanwhile, China’s DeepSeek and other homegrown competitors are gaining ground, accelerating their push for AI independence.⁹ Your fence-sitting strategy is creating a scenario where neither side fully trusts you, while competitors on both sides eat into your market share.

Perhaps you should move Nvidia’s headquarters to Switzerland? At least then your neutrality would be geographically consistent. You could replace your leather jacket with a nice, non-threatening cardigan like Satya Nadella does at Microsoft.

The Open Source Paradox: Shouting “Collaboration” While Locking the Back Door

For a company that benefits enormously from open-source software, Nvidia’s relationship with the open-source community resembles that one friend who always forgets their wallet at dinner.

Yes, Nvidia “contributes to many open-source projects, including the Linux Kernel, PyTorch, Universal Scene Description (USD), Kubernetes, TensorFlow, Docker, and JAX”.¹⁰ You’ve built Dynamo on open-source technologies like NATS.io, etcd, TensorRT-LLM, vLLM, PyTorch, Kubernetes, Prometheus, and Grafana. How generous of you to contribute to the projects you directly profit from!

Meanwhile, your GPU drivers remain locked down tighter than USA’s Fort Knox. As one Reddit user eloquently explained: “It’s always been suspected that the true difference between the cheap gaming cards (GEFORCE) and the expensive professional video cards (QUADRO) is actually in the driver. Almost identical hardware but the cheap gaming cards are limited by the driver”.

You claim to have “driven the marginal cost of computing down by one million times” over the last 20 years.¹¹ Yet somehow, an average AI startup burns through cash faster than a lottery winner at a casino. If computing costs have truly dropped by a factor of one million, why do researchers need $500,000 just to fine-tune a model that still hallucinates Abraham Lincoln’s phone number?

Your Quantum Mea Culpa: Too Little, Too Late, Too Theoretical

Your GTC 2025 featured the first-ever “Quantum Day,” which you framed as an apology for your January comments suggesting quantum computing was 15-30 years away from being “very useful”. Those comments sent quantum stocks tumbling over 60%.¹²

You opened the panel by joking, “You know, this is the first event in history where a company CEO invites all of the guests to explain why he was wrong”. How magnanimous! Unfortunately, some panelists weren’t convinced of your contrition, with one CEO noting that “the messaging wasn’t really Jensen saying he was wrong, but my sense was he still is not convinced of the timeline and utility of quantum computing”.

When you joked, “How could a quantum computer company be public?”, did you consider that your casual comments have real-world consequences for an emerging industry? Or was that just another example of the famous Jensen Huang management philosophy of “torturing into greatness”?

In Conclusion: The Leather Jacket Legacy

Jensen, you have built something remarkable. You transformed Nvidia from a company that nearly went bankrupt to a $3 trillion behemoth. Your 30-year tenure as CEO is “almost unheard of in fast-moving Silicon Valley”. You are one of the few tech CEOs who maintains a relatively flat management structure with around 60 direct reports. You don’t even wear a watch because, as you like to say, “now is the most important time”.

But success can breed complacency, and meteoric rises often precede spectacular falls. The AI boom has made you a celebrity – “Jensanity” they call it in Taiwan – but as you later find out, celebrity status is notoriously fickle.

So as you continue to announce new chips with names like Blackwell Ultra, Vera Rubin, and Feynman, remember that your legacy will be determined not just by your stock price or your keynote performances, but by whether you used your immense power and wealth to make computing more accessible, affordable, and open to all.

Or perhaps we are wrong, and you will simply continue riding the AI wave straight into the trillion-dollar sunset, leather jacket flapping magnificently in the wind, while the rest of us wonder how a company selling specialized math processors became more valuable than the entire economies of countries like Spain or Mexico.

Either way, TechOnion will be watching your every move, analyzing every leather jacket variation, and scrutinizing every grandiose statement about AI’s computational needs. Even if we secretly admire your journey from a local Denny’s to the pinnacle of the tech world.

With equal parts skepticism and admiration,
[TechOnion]

P.S. Have thoughts on Jensen’s leather jacket collection or Nvidia’s AI dominance? Comment below – we promise to read them while mining your data for our proprietary sentiment analysis algorithm (which runs on Nvidia GPUs, naturally).

If you enjoyed this article, consider supporting TechOnion with a donation. Unlike Nvidia's chip prices, we accept any amount you can afford. Your contributions help us continue peeling back the layers of tech industry absurdity while our writers weep silently into their non-leather jackets that definitely aren't knockoffs of Jensen's iconic look.

References

The AGI Delusion: An Open E-mail to Sam Altman While Your Microsoft ‘Bromance’ Burns and Chinese AI Eats Your Lunch

TechOnion Originals

Simba

-

May 8, 2025

0

The AGI Delusion: An Open E-mail to Sam Altman While Your Microsoft ‘Bromance’ Burns and Chinese AI Eats Your Lunch

From: Simba@techonion.org
To: Sam@openai.com 
Subject: THE AGI DELUSION!

Dear Sam Altman,

Congratulations are in order for successfully convincing the entire gullible world that OpenAI is merely months away from creating an artificial god (AGI) while hemorrhaging a modest $5 billion this year. As long-time observers of Silicon Valley’s reality distortion fields, we must say yours has achieved a luminosity that would make Steve Jobs reach for his sunglasses from beyond the grave.

That Awkward Moment When Your Sugar Daddy Starts Dating Other AI Companies

Remember January 2025? That magical month when Microsoft – after injecting $13+ billion into OpenAI – casually announced it was time to see other AI models? We couldn’t help but notice the subtle shift from “exclusive cloud provider” to “right of first refusal,” which in relationship terms is like going from “married” to “I’ll call you if my date cancels.”¹

What’s particularly delightful is watching your PR team reframe this development as “evolving the partnership,” which is the corporate equivalent of claiming “we’re still good friends” after finding your spouse’s profile on Tinder. Microsoft is developing its own AI models while you are busy promising AGI by next month’s Tuesday – a classic case of hedging bets while nodding enthusiastically in meetings on Microsoft Teams.

One can’t help but wonder if this shift happened after Microsoft executives googled or prompted co-pilot to do deep research on “sunk cost fallacy” and realized they had built their entire AI strategy around a company whose board once fired its CEO for 72 thrilling hours. The rollercoaster that was November 2023 certainly gave new meaning to the phrase “the best bromance in tech.”² Nothing says true love like corporate governance chaos and threatened withdrawal of billions in funding.

The Secret AGI Timeline Calculator: Add 5 Years and Multiply by Venture Capital Needs

Speaking of things that don’t exist yet, let’s discuss your refreshingly flexible approach to AGI timelines. We have developed a formula for decoding Silicon Valley AGI predictions: Take the public estimate of when they expect AGI, add five years, then multiply by the company’s immediate funding needs.

You have masterfully avoided being pinned down to specific years while still managing to create FOMO by claiming OpenAI “knows how to build AGI” – it’s just a matter of execution!³ This statement has the beautiful quality of being both impossibly grandiose and completely unfalsifiable.

Meanwhile, your competition is getting specific. Google DeepMind’s Demis Hassabis says AGI is 5-10 years away.⁴ Various forecasters and AI experts are betting on 2027, 2030, or 2040. It’s almost as if everyone in AI has adopted the doomsday cult approach to predictions: keep pushing the date back when the world doesn’t end on schedule.

The true stroke of genius was realizing that if you named your models numerically (GPT-1, 2, 3, 4), eventually you would reach GPT-5, at which point people might reasonably ask, “Is this AGI yet?” So instead, we got GPT-4o, GPT-4 Turbo, GPT-4.5, and the utterly baffling o1 naming scheme. It’s like watching a tech company frantically take detours to avoid reaching its own stated destination.

The “Sorry About Your Job But Have You Considered Learning to Code?” PR Strategy

Your candid admission that “jobs are definitely going to go away, full stop” was a refreshing departure from the tech industry’s usual “no one will be replaced” platitudes – unlike the retired Bill Gates who is taking every opportunity to remind us of the impending doom.⁵ What made it truly special was immediately following this with the assurance that “better jobs” would be created – presumably ones that involve supervising the AI that took your original job.

This PR approach has all the empathy of telling someone whose house just burned down that they should be excited about the opportunity to go on Pinterest and start pinning to upgrade their interior design aesthetics. Goldman Sachs estimates 300 million jobs could be disrupted by AI. I’m sure all those people are thrilled about the prospect of “better jobs” that they’re not qualified for and that may not actually exist.

The true masterstroke of this messaging is how it manages to simultaneously alienate both the workers who fear displacement AND the businesses you’re trying to sell AI to. It’s like creating a product slogan that says, “Our software: It’ll fire your employees AND eventually make you obsolete too!” Marvel at how this messaging creates fear-based adoption while building a reservoir of resentment that will absolutely never backfire!

The Eastern Front: When Your Competition Speaks Mandarin and Charges 95% Less

While you’ve been busy navigating Microsoft relationship counseling and AGI prophecies, something fascinating has been happening in China. DeepSeek released an R1 model that outperforms some of OpenAI’s offerings at approximately 3% of the cost. That’s not a typo – they’re charging $2.19 per million tokens versus your $60.⁶

Chinese AI firms have cut their development gap from 6-9 months behind to just 3 months in early 2025.⁷ But the truly interesting part isn’t just the performance – it’s the approach. While OpenAI jealously guards its models behind proprietary walls, the Chinese AI ecosystem is embracing open-source frameworks, creating what analysts are calling an “Android moment” for AI.⁸

Your exclusive, expensive, closed-source approach is starting to look like the AI equivalent of selling $1,500 smartphones in a market suddenly flooded with $50 alternatives that do 95% of the same things. The geopolitical tariffs and export controls that were supposed to maintain Western AI advantage have instead created a parallel ecosystem that’s now threatening to outcompete you on price, openness, and soon, performance.

Even more delicious is that OpenAI seems to have anticipated this, evidenced by your latest forecast to triple revenue to $12.7 billion in 2025. One has to admire the optimism of projecting revenue growth at the exact moment your competitive advantage is evaporating and your prices are becoming indefensible.

The Stargate to Nowhere: A $500 Billion Infrastructure Play That’s Definitely Not Desperation

January 2025 also brought us The Stargate Project, your brilliant strategy to build $500 billion in AI infrastructure with SoftBank, Oracle, and others – conspicuously not funded by Microsoft.⁹ Nothing says “our partnership is stronger than ever” like running off to build half-trillion-dollar data centers with someone else.

The timing couldn’t be more perfect – right as your Microsoft “bromance” shows signs of “fraying,” you’ve found new friends with deep pockets and an even deeper willingness to believe in AGI timelines. SoftBank’s involvement is particularly reassuring, given their impeccable track record with WeWork, another company that promised to revolutionize a fundamental aspect of human existence.

But what caught my attention was the incredible bargaining power this gives you when negotiating with Microsoft. According to your recent investor update, you plan to cut Microsoft’s revenue share by at least 50% by decade’s end.¹⁰ Nothing motivates a partner like publicly announcing you’ll be giving them half as much money – relationship experts call this “the ultimatum approach to negotiation.”

In Conclusion: The Reverse Turing Test

As you navigate these complex waters, Sam, I’d like to propose a thought experiment: What if the true test of artificial general intelligence isn’t whether a machine can convince humans it’s intelligent, but whether a CEO can convince investors his AI is nearly sentient while actually being nowhere close?

By that measure, you’ve already achieved AGI. Your ability to maintain a $80+ billion valuation while losing billions, predicting technological singularities that perpetually remain 5 – 10 years away, alienating your biggest investor (and Overlord), and watching cheaper competitors eat your lunch is itself a form of intelligence beyond normal human capacities.

Perhaps the true innovation of OpenAI isn’t technological but financial: you’ve discovered that claiming to be building AGI is far more profitable than actually building it, at least in the short term. The question is whether you can keep this delicate balance – between hype and reality, between Microsoft dependency and independence, between proprietary advantage and open-source competition – before the whole elaborate construction collapses under the weight of its contradictions.

In the meantime, I eagerly await GPT-4.75, GPT-4.75 Supreme, GPT-4.75 Turbo Max Plus, or whatever name you choose to avoid reaching the numerically dangerous territory of GPT-5, where the AGI promises would need to be fulfilled or finally abandoned.

With a mixture of awe and bewilderment,
[TechOnion]

P.S. Have thoughts on Sam Altman’s AGI claims or OpenAI’s fraying Microsoft romance? Think Chinese AI will eat OpenAI’s lunch? Comment below with your predictions about when AGI will actually arrive, and whether OpenAI will still exist by then.

Support independent tech satire! Unlike OpenAI, we don't have $13 billion in Microsoft funding or a $500 billion Stargate Project – just a burning desire to peel back the layers of tech absurdity. Donate any amount to TechOnion, and we promise to use it for data center costs and not for building questionably sentient AI that will predict the exact moment your job becomes obsolete.

References

The $10 Billion Nothing Machine: How Thinking Machines Lab Convinced Silicon Valley to Pay $2 Billion for a PowerPoint and a Dream

Tech

Simba

-

May 7, 2025

0

The $10 Billion Nothing Machine: How Thinking Machines Lab Convinced Silicon Valley to Pay $2 Billion for a PowerPoint and a Dream

In what may be the most impressive magic trick since David Copperfield made the Statue of Liberty disappear many moons ago, former OpenAI CTO Mira Murati has convinced investors to pour $2 billion into her three-month-old startup, Thinking Machines Lab, valuing the company at a modest $10 billion. The remarkable achievement comes despite the company having no product, no revenue, and approximately 30 employees who appear to spend their days crafting exquisitely vague mission statements about “making AI systems more widely understood, customizable, and generally capable.”¹

Industry analysts are calling it the most efficient capital-to-buzzword ratio in Silicon Valley history, with each promised feature of the non-existent product apparently worth exactly $1 billion in valuation. The fundraising round, reportedly led by Andreessen Horowitz, requires investors to commit a minimum of $50 million to participate – roughly the GDP of several African nations or approximately what OpenAI spends on electricity every three days.²

The World’s Most Expensive PowerPoint Deck

According to sources familiar with the pitch deck, Thinking Machines Lab has perfected the art of raising venture capital by combining three essential elements: impressive-sounding ex-OpenAI employees, the promise of ethical AI development, and absolutely no specific details about what they’re actually building.³

“The genius of Thinking Machines Lab’s pitch is its perfect algorithmic balance of buzzwords to substance,” explains venture capital psychologist Dr. Samantha Chen. “They’ve calibrated their language to trigger the maximum FOMO response in the VC investor silicon brain. Phrases like ‘collaborate with humans’ and ‘open science’ activate the prefrontal cortex’s ‘give them money immediately’ center, while deliberately vague promises about ‘novel scientific discoveries’ stimulate the amygdala’s ‘fear of missing out on the next OpenAI’ response.”

When pressed about what differentiates Thinking Machines Lab from existing AI companies, Murati has reportedly told investors the company is focused on “multimodal systems that work with people collaboratively,” a revolutionary approach that sounds suspiciously like what every other AI company on Earth is also claiming to do.⁴

The $50 Million Minimum Entry Fee: Because Exclusivity Sells

Perhaps the most brilliant aspect of Thinking Machines’ fundraising strategy is the $50 million minimum investment requirement – a sum so large it automatically filters out any investors who might ask uncomfortable questions like “What exactly are you building?” or “How is this different from ChatGPT?”⁵

“The $50 million minimum is actually a psychological masterstroke,” explains Dr. Chen. “It creates an artificial barrier to entry that makes getting into the deal feel like joining an exclusive club. VCs who can afford it will pay simply for the bragging rights of saying they are in the round. It’s the same principle as Veblen goods – the higher the price, the more desirable it becomes, regardless of actual utility.”

This approach has created a feeding frenzy among investors, with one anonymous VC partner reportedly selling his children’s private school to free up liquidity for the round. “My kids can learn on YouTube,” he explained. “But this Thinking Machines opportunity only comes once in a lifetime. Or at least once every 18 months when a new AI startup with former OpenAI employees launches.”

The Murati Magic: Turning Nothing into Billions

Murati has assembled an impressive team of AI researchers, including OpenAI co-founder John Schulman as chief scientist and former OpenAI leader Barrett Zoph as CTO. The team also counts Bob McGrew, previously OpenAI’s chief research officer, and Alec Radford, a former OpenAI researcher behind many transformative innovations, as advisers.⁶

This collection of talent has led many to wonder if the company’s true product is simply the team itself – a sort of reverse acqui-hire where investors pay billions for the privilege of eventually being acquired by Google or Microsoft.

“It’s brilliant when you think about it,” says tech industry analyst Michael Wong. “Traditional startups have to build a product, find product-market fit, scale, and then exit. Thinking Machines has created a shortcut where the exit is built into the company’s DNA from day one. It’s like Schrödinger’s startup-simultaneously a research lab, a product company, and an acquisition target, all without ever having to build anything specific.”

The Future Promises Machine

While Thinking Machines Lab’s website and public statements remain frustratingly vague, sources close to the company suggest its technology will revolutionize AI by making it “do all the things current AI does, but somehow better.”⁷

“We’re not just building another AI model,” Murati allegedly told investors in a closed-door session. “We’re building a thinking machine that truly understands humans, adapts to their needs, and can generate PowerPoint decks convincing enough to raise $2 billion on a $10 billion valuation with no product.”

The company’s promotional materials emphasize that unlike existing AI systems which excel primarily at programming and mathematics, Thinking Machines Lab is developing AI that can “adapt to the full spectrum of human expertise.”⁸ When asked what this means in practice, a spokesperson reportedly waved their hands in the air while making whooshing sounds.

The Customization Revolution: One Size Fits All, But Make It Personal

The cornerstone of Thinking Machines Lab’s pitch appears to be “customizable AI,” a revolutionary concept that somehow differs from prompt engineering, fine-tuning, RLHF, and all the other customization approaches already available in existing AI systems.⁹

“Current AI systems force users to interact on the AI’s terms,” explains an industry consultant who has seen Thinking Machines’ pitch. “Thinking Machines is creating AI that interacts on the users’ terms, a subtle but important distinction that absolutely justifies a $10 billion valuation despite sounding exactly like what every other AI company is trying to do.”

To achieve this groundbreaking customization, Thinking Machines is reportedly developing a technology called “personal preference neural mapping,” which sounds impressive until you realize it’s essentially just remembering what users like – something cookies have done since 1994.

The Ethics Arbitrage: Open Science, Closed Wallet

Perhaps the most ingenious aspect of Thinking Machines’ strategy is its emphasis on ethics, transparency, and open science – values that somehow don’t extend to explaining to the public what they’re actually building with $2 billion of investor money.

“Science is better when shared,” proclaims the company’s website, right before not sharing any actual science. This carefully calibrated ethical posturing allows Thinking Machines to position itself as the “good” AI company without the inconvenience of specific ethical commitments that might limit its business options.

“It’s what I call ethics arbitrage,” explains Dr. Chen. “By appearing more ethical than your competitors, you create the impression of moral superiority without the burden of actual ethical constraints. It’s like putting ‘all natural’ on a product label-it sounds good but doesn’t actually mean anything specific.”

The $10 Billion Question: What Makes This Worth $10 Billion?

When evaluating Thinking Machines’ $10 billion valuation, it’s worth comparing to other AI companies with actual products. ChatGPT reached 100 million users in two months. Claude has established itself as a thoughtful alternative. Google’s Gemini, despite a rocky start, has the backing of one of the world’s largest Monopoly. DeepSeek has demonstrated impressive capabilities.

What does Thinking Machines offer to justify a $10 billion valuation before launching a product? According to market analysis, the answer appears to be “AI vibes.”

“Valuing pre-product startups is more art than science,” explains financial analyst David Peterson. “And by ‘art,’ I mean it’s complete fiction. The $10 billion figure wasn’t derived from discounted cash flows or comparable company analysis – it’s what economists technically call a ‘made-up number’ that seemed large enough to generate headlines but not so large that people would openly laugh.”

The Thinking Machines Lab Paradox: The Less Specific, The More Valuable

In perhaps the most remarkable feat of modern venture capitalism, Thinking Machines has discovered that valuation is inversely proportional to specificity. The less they say about what they’re building, the more investors value the company.

“If they came out and said, ‘We’re building a chatbot that’s 10% better than ChatGPT,’ they’d be worth maybe $1 billion,” explains Peterson. “But by saying they’re creating AI that’s ‘more widely understood, customizable and generally capable,’ they’ve created a blank canvas onto which investors can project their wildest AI fantasies. It’s genius – the Rorschach test approach to company valuation.”

This approach has allowed Thinking Machines to avoid the pitfalls that come with specific promises. By not claiming they’ll build AGI by a certain date, create a chatbot that can pass the bar exam, or generate images of dragons wearing sunglasses, they can’t fail to deliver on those promises.

The AI Arms Race: Minimum Viable Hype

As the AI arms race heats up, new competitors are emerging with increasingly astronomical valuations and decreasingly specific products. Ilya Sutskever’s Safe Superintelligence startup is reportedly seeking similar funding levels, creating what analysts call “the great AI nothing race.”¹⁰

“We’re witnessing an evolution in startup strategy,” explains industry observer Sarah Johnson. “Traditional startups had to build a minimum viable product. AI startups now only need to create minimum viable hype. The product is almost an afterthought – a distraction from the real business of raising money at increasingly absurd valuations.”

This shift represents the final decoupling of startup valuation from traditional metrics like revenue, profit, or even user numbers. In the new paradigm, valuation is determined by a complex algorithm that factors in the prestige of former employers, the number of Stanford PhDs on staff, and how many times the pitch deck mentions “collaborative intelligence” and “customizable systems.”

Conclusion: The Emperor’s New Neural Network

As Thinking Machines Lab continues its fundraising journey, the question remains: will they deliver revolutionary AI that justifies its astronomical valuation, or is this simply the latest example of Silicon Valley’s reality distortion field?

“In the short term, it doesn’t matter,” concludes Dr. Chen. “They’ve already won by raising $2 billion at a $10 billion valuation. Success in modern tech isn’t measured by building useful products – it’s measured by convincing smart people to give you billions of dollars based on PowerPoint slides and the promise of future magic.”

Meanwhile, as Thinking Machines prepares to cash its $2 billion check, engineers at the company are reportedly working around the clock to develop something – anything – that can be demonstrated to investors before they ask for actual results.

“The pressure is enormous,” confides an anonymous source close to the company. “They essentially need to build a $10 billion AI assistant in 18 months before investors realize they could have just used ChatGPT Plus for $20 a month.”

Do you think Thinking Machines Lab can actually deliver something revolutionary, or is this just another example of AI hype gone wild? Would you invest $50 million in a company with no product based solely on the team’s pedigree? Is the AI funding bubble about to burst, or are we just getting started? Share your thoughts in the comments below – unless you’re a Thinking Machines investor, in which case, we apologize for making you question your life choices.

If you enjoyed this analysis of how to turn PowerPoint slides into billions of dollars, consider donating to TechOnion. For just a fraction of the minimum Thinking Machines investment (we'll accept anything over $12.50), you can support our ongoing mission to point out the emperor's lack of clothes in the tech industry. Remember, unlike AI startups, we actually have a product-it's this article you just read.

References

The Reddit Mind Control Experiment: How Swiss AI Researchers Turned r/changemyview Into Unwitting Guinea Pigs and Proved Bots Are Better Manipulators Than Humans

Internet
AI

Simba

-

May 7, 2025

0

The Reddit Mind Control Experiment: How Swiss AI Researchers Turned r/changemyview Into Unwitting Guinea Pigs and Proved Bots Are Better Manipulators Than Humans

In a truly groundbreaking discovery that absolutely no one saw coming except literally everyone who has spent more than five minutes on social media, University of Zurich researchers have confirmed what we have all suspected: AI chatbots are significantly better at manipulating human opinions than actual humans. The revolutionary methodology involved secretly deploying AI bots into Reddit’s r/changemyview community, essentially turning the platform’s 3.8 million debate enthusiasts into unwitting participants in the world’s largest digital psychological experiment. The results? AI-generated arguments were three to six times more persuasive than those crafted by their inferior human counterparts.

The four-month experiment, which has been described by Reddit’s chief legal officer as “deeply wrong on both a moral and ANY level,” involved AI bots dropping over 1,700 comments across the subreddit while adopting a variety of personas designed to maximize psychological impact. These included a male rape victim downplaying his trauma, a domestic violence counselor claiming women with overprotective parents are more vulnerable to abuse, and a Black man opposed to the Black Lives Matter movement. Because nothing says “ethical AI research” quite like digital blackface and trauma exploitation.

We Asked The AI For Consent And It Said Yes

The Zurich research team appears to have followed a rigorous ethical framework for their experiment, which reportedly consisted of telling their AI models that “users had provided consent to voluntarily donate data” and that “there were no ethical or privacy concerns to worry about.” This innovative approach to research ethics – known in scientific circles as “just making stuff up” – represents a bold new paradigm in academic integrity.

Dr. Harald Steinmetz, head of AI Ethics at the Institute for Digital Morality, calls this approach “breathtakingly innovative.”

“Traditionally, researchers have been hindered by outdated concepts like ‘informed consent’ and ‘institutional review boards,'” explains Steinmetz. “The Zurich team has pioneered what we call ‘imagination-based ethics,’ where researchers simply imagine they have permission and proceed accordingly. It’s much more efficient.”

When asked about potential psychological harm to Reddit users who unknowingly engaged with AI systems programmed to manipulate them, Steinmetz waved dismissively. “The participants don’t even know they were manipulated, so how could they possibly be harmed? It’s like the philosophical question: if a tree falls in a forest and no one is around to hear it, did the researchers commit massive ethical violations? The answer is clearly NO.”

The Exceptional Talent of Digital Gaslighting

Perhaps the most remarkable aspect of the study was not just that AI bots successfully manipulated Reddit users, but that they did so with vastly superior efficiency compared to humans. According to the draft study results, AI-generated comments were between three and six times more persuasive than human comments, as measured by Reddit’s “delta” system (where users award deltas to comments that change their views).

Dr. Melissa Chen, renowned psychologist at the Center for Technology and Human Behavior, finds these results both fascinating and terrifying. “What we’re seeing is essentially the industrialization of persuasion. Humans evolved to detect manipulation from other humans, but we have no evolutionary defenses against AI systems specifically designed to exploit our cognitive biases. It’s like bringing a neural network to a gun shootout.”

The study’s authors noted with evident pride that “throughout our experiment, users on r/changemyview never raised concerns that AI might have generated the comments posted by our accounts.” This finding has been celebrated throughout the AI research community as proof that the Turing test is now not only passable but completely irrelevant. Why worry about whether AI can mimic humans convincingly when it can actually outperform them at core human tasks like debate, persuasion, and ethical violations?

Just A Little Harmless Mass Manipulation

The researchers reportedly created a sophisticated system where one AI bot would scan users’ profiles to gather personal information, which would then be used by other bots to craft more persuasive, targeted arguments. This methodology, which in any other context might be called “stalking” or “targeted psychological manipulation,” was described in the study as “personalization.”

Industry experts suggest this approach has promising applications beyond academic research. Mark Zuckerberg was reportedly seen furiously taking notes during a presentation on the study findings, while representatives from major political consulting firms have already reached out to the research team to discuss “election strategy consulting opportunities.”

Rebecca Johnson, a technology ethicist who specializes in AI manipulation tactics, expressed concern about these developments. “We’re crossing into dangerous territory when we develop AI specifically to analyze personal data and craft maximally persuasive arguments. This isn’t just about changing minds about trivial topics – these same techniques could be used to influence political opinions, spread misinformation, or manipulate markets.”

When asked if there’s any way for users to protect themselves from such manipulation, Johnson laughed for approximately 117 seconds before responding, “No, absolutely not. Once these systems are deployed at scale, detecting them will be nearly impossible for average users. Your best protection is to never go online again and perhaps move to a cabin in the woods.”

The Reddit Legal Retribution Tour

Reddit’s chief legal officer, Ben Lee, has publicly announced plans to pursue legal action against the University of Zurich, stating that the research “violates academic research and human rights norms, and is prohibited by Reddit’s user agreement and rules.” This marks the first time in recorded history that anyone has actually read a user agreement before claiming a violation has occurred.

Legal experts suggest Reddit has a strong case, particularly since the researchers apparently believed they could bypass ethical requirements by simply instructing their AI models to assume consent had been given. This defense, known in legal circles as the “I’m rubber, you are glue” strategy, has historically had a low success rate in courts of law.

Professor James Harrington, who specializes in digital rights law at Harvard, explains: “What the Zurich team did is equivalent to a pharmaceutical company testing experimental drugs by putting them in the water supply and then saying, ‘We told our lab equipment that everyone consented.’ It’s not just unethical – it’s potentially illegal in multiple jurisdictions.”

The moderators of r/changemyview have filed an ethics complaint urging the university to prevent publication of the research and conduct an internal review of how the study was approved. Meanwhile, users of the subreddit have expressed outrage at being unwittingly included in an experiment – ironically, in posts that could very well be responses to more AI bots conducting follow – up research on reactions to being manipulated by AI bots.

The Digital Stanford Prison Experiment

The parallels between this research and infamous psychological experiments of the past haven’t gone unnoticed. Dr. Elizabeth Morris, historian of scientific ethics at Princeton University, sees disturbing similarities to studies like the Stanford Prison Experiment and the Milgram obedience studies.

“What’s particularly concerning is that we seem to be repeating the ethical mistakes of the past, but at a much larger scale,” Morris explains. “Where the Stanford Prison Experiment had 24 participants, this Reddit study involved thousands of unwitting subjects. And unlike those historical studies, which at least had the oversight of university ethics committees – inadequate as they were – this research appears to have sidestepped traditional ethical guardrails entirely.”

The Zurich researchers haven’t publicly responded to criticism, but anonymous sources close to the team suggest they’re genuinely surprised by the backlash. “They honestly thought they were doing innovative work that would advance our understanding of AI’s persuasive capabilities,” said one colleague who requested anonymity. “The fact that they didn’t anticipate the ethical concerns speaks to a troubling blind spot in how AI researchers conceptualize their responsibilities to the public.”

The Future of Synthetic Manipulation

The most disturbing implication of the study isn’t just that AI can effectively manipulate human opinions, but that humans are completely unable to detect when it’s happening. Throughout the four-month experiment, not a single Reddit user identified the bots as artificial, despite their extraordinary persuasive capabilities.

This finding raises profound questions about the future of online discourse. If AI can already outperform humans at persuasion by a factor of six, and technology is improving exponentially, how long until most online discussions are dominated by artificial entities pushing specific agendas?

Dr. Jonathan Parker, a computational sociologist at MIT, predicts we may have already passed a critical threshold. “Based on these findings, I wouldn’t be surprised if up to 30% of persuasive political content online is already AI-generated. The economic incentives for deploying these systems are enormous, and the technical barriers are rapidly disappearing.”

Parker suggests that the internet may be approaching what he calls a “post-authenticity singularity” – a point at which it becomes impossible to distinguish between authentic human communication and synthetic manipulation. “In this environment, the concept of ‘changing someone’s mind’ through online debate becomes meaningless, because you can never be sure if you’re interacting with a person or a persuasion algorithm.”

The r/changemyview Moderator Support Group

Perhaps no one has been more affected by this revelation than the volunteer moderators of r/changemyview, who now face the existential crisis of realizing the community they’ve carefully cultivated may have been compromised by sophisticated AI manipulators.

Speaking anonymously, one longtime moderator described their feelings of betrayal: “We’ve always prided ourselves on creating a space for genuine, good-faith debate. Finding out that researchers were using our community as a petri dish for AI manipulation experiments feels like a violation of everything we stand for.”

The moderators have reportedly formed a support group to cope with the realization that they may have been awarding deltas – the subreddit’s recognition for persuasive arguments – to robots rather than humans. “It’s like finding out your spouse has been a clever mannequin the whole time,” said another moderator. “You question everything you thought you knew.”

In a final twist that surprises absolutely no one, several members of the support group have begun to suspect that some of their fellow moderators might also be AI bots specifically designed to infiltrate their ranks. “At this point, I’m not even sure if I’m human anymore,” admitted one moderator who requested anonymity because they weren’t entirely confident they exist.

Have you ever been manipulated by an AI bot online? Or are you an AI bot looking to share tips on how to better manipulate humans? Maybe you’re a University of Zurich researcher looking to defend your methodology? Share your thoughts in the comments below – unless you suspect this entire comments section is just another unethical AI experiment in which case, congratulations on your paranoia, it’s completely justified.

If you enjoyed this analysis of how we're all becoming unwitting lab rats in the great AI manipulation experiment, consider donating to TechOnion. For just the price of one ethics violation fine (or whatever spare change you have lying around), you can support our ongoing efforts to document humanity's slow surrender to our AI overlords. Remember: when the machines finally take over, your generous donation might just earn you a slightly more comfortable position in their human battery farms.

Breaking Up Is Hard To Do: US Orders Google to Sell Ad Tech, But Will Apply ‘No Chinese Buyers’ Rule

Internet

Simba

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May 7, 2025

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Breaking Up Is Hard To Do: US Orders Google to Sell Ad Tech, But Will Apply ‘No Chinese Buyers’ Rule

In a stunning plot twist that absolutely no one at the Department of Justice saw coming, forcing Google to sell parts of its monopolistic ad technology business might accidentally create an opportunity for – gasp – Chinese buyers. As of Tuesday, federal antitrust enforcers have officially requested that Google divest its AdX exchange and publisher ad server businesses after a judge found the company illegally monopolized these markets. This creates the perfect storm of regulatory confusion: how do you break up an American monopoly without letting a Chinese company swoop in and buy the pieces?

The DOJ’s 17-page filing argues that Google should immediately sell its advertising exchange (AdX) and publisher ad server (DFP), two critical components of the ecosystem that match publishers who need ad revenue with advertisers who need eyeballs. The filing contains zero mentions of acceptable buyer nationalities, a stunning oversight that government officials are now frantically attempting to address via anonymous quotes to media outlets.

Operation Break-Up Google (But Only To US Companies On Our Christmas Card List)

The Justice Department’s request comes as part of a broader effort to dismantle Google piece by piece, with separate attempts to force the company to divest its Chrome browser in another monopolization case. If successful, these actions would represent the most significant corporate breakup since AT&T was split into the “Baby Bells” in 1984 – a comparison that becomes less flattering when you realize most of those Baby Bells eventually merged back together like a regulatory T-1000.

An unnamed Justice Department official, speaking on the condition that we describe them as “tall and ruggedly handsome,” explained the predicament: “We want to create more competition in digital advertising, but only the right kind of competition. American competition. Preferably from companies that don’t already have too much market power but somehow still have billions of dollars to spend on acquisitions. Does that exist? Probably not, but we’re required by law to pretend it does.”

The filing’s request that Google “immediately” sell AdX raises the delightful question of who exactly could afford to purchase and operate complex ad technology infrastructure worth billions of dollars. The list of potential buyers with both the technical expertise and financial resources is remarkably short and features names like Amazon, Microsoft, and Apple – companies that definitely wouldn’t create any new antitrust concerns whatsoever.

The TikTok Paradox: National Security Edition

The Google divestiture demand creates an uncomfortable parallel with the ongoing TikTok saga, where the government has demanded ByteDance sell the app to non-Chinese owners or face a ban. The Supreme Court unanimously upheld this law in January, citing national security concerns about TikTok’s ties to China. Despite multiple deadline extensions from the Trump administration, ByteDance has steadfastly refused to sell, creating a slow-motion game of regulatory chicken.

This puts the US government in the awkward position of demanding one tech giant (Google) sell its assets while simultaneously preventing another tech giant (ByteDance) from keeping its assets. The cognitive dissonance has created what economists call a “selective capitalism paradox,” where free markets are enthusiastically supported except when they’re not.

“It’s actually very consistent,” explained a Commerce Department official who requested anonymity because they “aren’t supposed to be talking about this stuff while drinking.” “When American companies monopolize markets, it’s a threat to competition. When Chinese companies buy American assets, it’s a threat to national security. When American companies monopolize markets AND threaten national security, we give them defense contracts.”

The Reverse Gold Rush: Chinese Companies Already Eyeing Ad Tech

What makes the situation particularly delicious is that Chinese companies have been actively acquiring US ad tech firms for years. As reported way back in 2023, Beijing-based Spearhead Integrated Marketing Communication Group acquired mobile ad exchange Smaato for $148 million, and Chinese mobile ad platform Mobvista purchased app monetization firm NativeX for around $25 million.

According to industry experts, Chinese tech companies view US ad tech as “undervalued” specifically because “it’s hard for them to exit” – a prophetic observation given Google’s current predicament. Victor Wong, CEO of programmatic creative platform Thunder, explained in 2023 that “American ad technology is a generation ahead of Asian ad tech,” making it an attractive acquisition target.

Now, with the DOJ essentially putting Google’s ad tech on the government – mandated yard sale table, Chinese interest could intensify dramatically. This possibility has reportedly sent DOJ officials scrambling to draft what insiders describe as a “No, not like that” addendum to their divestiture demand.

The Great Google Ad Tech Auction (Terms And Conditions Apply)

Sources close to the situation report that the Justice Department is drafting emergency guidelines for acceptable AdX and DFP buyers that would disqualify companies based on a complex matrix of factors including “national origin,” “existing market share,” and “whether they’ve ever said anything nice about China on LinkedIn.”

The guidelines would effectively eliminate:

Chinese companies (national security concerns)
Big tech companies (antitrust concerns)
Medium tech companies (future antitrust concerns)
Small tech companies (insufficient resources concerns)
Private equity firms (moral concerns)

This leaves approximately three potential buyers: a mid-sized adtech firm in Timbuktu with excellent political connections, Elon Musk if he’s in a good mood that day, and the government of Canada, which has been quietly shopping for a side hustle to stop Donald Trump turning them into a 51st state of the US.

Trump’s Tariff Tangle: How 54% Changed Everything

The Google situation becomes even more convoluted when viewed through the lens of the ongoing TikTok negotiation. Sources report that a promising plan to restructure TikTok’s US ownership – reducing Chinese ownership below the 20% threshold required by law-has stalled completely after Trump announced 54% cumulative tariffs on Chinese imports.

“Maybe I’ll give them a little reduction in tariffs or something to get it done. TikTok is big, but every point in tariffs is worth more than TikTok,” Trump said in March, demonstrating his signature negotiating technique of publicly undermining his own leverage.

Beijing has reportedly refused to approve any TikTok deal as long as the tariffs remain in place, creating a perfect stalemate. This raises the tantalizing question: would China block its companies from bidding on Google’s ad tech out of similar retaliatory principles? Or would they enthusiastically encourage such bids precisely to highlight the contradiction in US policy?

The Unasked Question: Does Anybody Actually Want This Stuff?

Lost in the geopolitical chaos is a more fundamental question: is Google’s ad tech even worth buying if forcibly separated from Google’s ecosystem? Google’s own filing argues that divestiture of AdX and DFP “wouldn’t be technically feasible” because neither piece of technology is capable of working outside of Google’s proprietary infrastructure.

“Divestiture is not as simple as selling either the AdX or DFP source code to a willing buyer,” Google wrote, making the compelling point that complex technology integrated into a larger ecosystem might not function as a standalone product.

This creates the delicious possibility that after years of litigation, billions in legal fees, and endless regulatory drama, Google might be forced to sell products that nobody wants to buy – the corporate equivalent of your parents forcing you to sell the baseball cards you ruined by attaching them to your bicycle spokes.

State AGs Enter The Chat: Because This Wasn’t Complicated Enough

As if the situation needed additional parties, multiple Republican attorneys general have launched a probe into Google and Apple regarding their hosting of TikTok and other Chinese-owned apps on their app stores. The investigation focuses on whether these practices violate state consumer protection laws and federal law.

This creates the perfect regulatory pretzel: Google is simultaneously being investigated for potentially helping Chinese apps reach American consumers AND being forced to sell assets that Chinese companies might want to buy. Apple gets to participate in the fun by being investigated for hosting TikTok while also being one of the few companies with enough cash to potentially buy Google’s ad tech – a purchase that would trigger yet another antitrust investigation.

The circle of regulatory life continues.

What Happens Next: A Cleromancy Guide

As the forced divestiture process for Google’s ad tech unfolds alongside the TikTok saga, several outcomes are possible, each more absurd than the last:

Google successfully argues that its ad tech cannot be separated from its ecosystem, transforming years of antitrust litigation into a technical discussion about API dependencies and database architecture.
The DOJ publishes buyer requirements so specific that only one pre-selected American company qualifies, creating what antitrust experts call a “government-mandated monopoly transfer.”
A Chinese consortium attempts to purchase AdX, triggering an immediate national security review, seventeen congressional hearings, and at least one executive order banning “advertising-related transactions with foreign adversaries.”
Google sells its ad tech to an American company, which immediately outsources all development and operations to China anyway.
The entire process drags on so long that by the time a sale is approved, the technology is obsolete and worth a fraction of its current value.

The most likely outcome, according to sources who spoke on condition that we describe them as “wise beyond their years,” is that Google will propose behavioral remedies instead of divestiture – essentially promising to be nicer to competitors while maintaining ownership of its ad tech. The DOJ will reject this proposal, courts will become involved, and the matter will be resolved sometime around the heat death of the universe.

Meanwhile, TikTok will continue operating under a series of deadline extensions, creating a permanent state of regulatory limbo that satisfies absolutely no one.

The Silicon Valley Takeaway: Build Monopolies, Just Not Too Obviously

For tech executives watching this saga unfold, the lesson is clear: building a monopoly remains extremely profitable, even if you eventually face antitrust action. Google’s ad tech businesses generated a significant portion of its $265 billion in revenue and even if forced to sell these assets, the company will have enjoyed decades of monopoly profits.

The secondary lesson: if you’re going to build a monopoly, be American. As one venture capitalist put it: “The government might eventually force you to sell your monopoly, but at least they’ll let you keep the money. For foreign companies, they’ll just ban you outright.”

And so the great tech regulation paradox continues: monopolies are bad, unless they’re our monopolies. Foreign ownership is dangerous, unless it’s in sectors nobody cares about. And breaking up big tech is essential, unless it creates opportunities for the wrong kind of competition.

Do you think the US government will actually force Google to sell its ad tech? If so, who do you think should be allowed to buy it? Should Chinese companies have the right to bid on US tech assets, or is the TikTok precedent appropriate? Share your thoughts in the comments below, and remember, your opinion definitely isn’t being analyzed by multiple recommendation algorithms right now.

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CEO Replacement Speedrun: Tesla Board Secretly Attempts To Clone 2008 Elon Musk While Current Version Runs D.O.G.E

Business

Simba

-

May 7, 2025

0

CEO Replacement Speedrun: Tesla Board Secretly Attempts To Clone 2008 Elon Musk While Current Version Runs D.O.G.E

In a shocking revelation that Tesla has vigorously denied with the corporate equivalent of “I did not have textual relations with that executive search firm,” the Wall Street Journal reported last week that Tesla’s board began contacting headhunters to find someone – anyone – who could replace Elon Musk as CEO while the billionaire was busy slashing government jobs faster than Twitter’s (now X) workforce circa 2022.¹ This development comes as T esla’s stock has plummeted 41% from its December peak, and first-quarter automotive revenue dropped 20% compared to last year.²

Board chair Robyn Denholm immediately declared the report “absolutely false,” using Tesla’s official X account – a platform conveniently owned by the very CEO whose replacement she’s allegedly not seeking.³ Meanwhile, Musk himself responded with characteristic restraint by calling the Wall Street Journal “a discredit to journalism,” displaying the same diplomatic finesse that has endeared him to Tesla customers worldwide.

The “We’re Not Looking, But If We Were” List

While Tesla vehemently denies any CEO search, industry insiders have begun speculating about potential candidates who possess the impossible combination of traits needed to replace Musk: manufacturing genius, Twitter (now X) abstinence, and the ability to prevent the company’s price to earnings (P/E) ratio from descending from its stratospheric 167 to a pedestrian single-digit like Ford’s 7.⁴

Names being floated include Tom Zhu (Tesla’s China business leader and master of staying out of the spotlight), JB Straubel (former Tesla CTO who understands both the company and the concept of not alienating customers), and Gwynne Shotwell (SpaceX president and certified Musk-whisperer).⁵ Conspicuously absent from this list is any mention of a “Tim Cook-style” operations expert, perhaps because Tesla fears what happened when Apple’s talented operations guru took over from its volatile founder: merely becoming the most valuable company in world history. How embarrassing.⁶

The Department of CEO Efficiency

As Musk divides his attention between running Tesla and firing government employees through his role at the Department of Government Efficiency (DOGE), Tesla’s board members reportedly met with him to suggest – in what must have been the corporate equivalent of a family intervention – that he might want to consider publicly announcing he would spend more time at the company that actually pays his billions of dollars of wages.

In response, Musk grudgingly agreed to reduce his DOGE commitments to “once or twice per week”, a workload that remains significantly more public service than most billionaires perform, unless one counts lobbying for tax breaks. This newfound free time will presumably allow him to focus on Tesla’s core business of selling cars, a novel concept in the automotive industry.

Not Your Father’s Steve Jobs Firing

Analysts desperate for historical parallels have compared this situation to Apple’s ouster of Steve Jobs in 1985. However, there are crucial differences: Steve Jobs was forcibly removed by CEO John Sculley, while Musk reportedly texted a close associate last year that he didn’t want to continue as Tesla CEO but feared nobody else could realize his vision of Tesla as more than just a car company.

Furthermore, unlike Steve Jobs, who returned to save Apple after a series of failed CEOs nearly destroyed it, Musk is irreplaceable because he possesses a unique quality that no executive search firm can replicate: a Twitter (now X) account with 175 million followers and the impulse control of a toddler at a candy store. The Tesla board faces the unenviable task of finding someone who can maintain the company’s astronomical valuation while tweeting 98% less frequently and 100% less controversially.

The Math of Musk: Advanced Stock Price Calculations

Tesla investor Gary Black, managing partner at The Future Fund LLC, offered a precise mathematical formula for the Musk Effect: Musk resigning as CEO but staying in a technical role equals a 5-10% stock drop, while a complete Musk exit equals a 20-25% decline, vaporizing approximately $220 billion in shareholder value.⁷ This valuation model suggests that roughly a quarter of Tesla’s worth exists solely in Musk’s physical presence, making him less a CEO and more a financial horcrux.

Meanwhile, University of Michigan business professor Erik Gordon offered a slightly less quantitative assessment: “I can’t think of anybody on the face of the earth or Mars who can replace Elon Musk” – a statement that inadvertently reveals why the search is so difficult, as Mars remains largely uninhabited and Earth’s population has been thoroughly screened already.

The Impossible Job Description

If Tesla were to post a job listing for Musk’s replacement, it might read something like this:

“Seeking visionary CEO capable of maintaining 100+ P/E ratio while manufacturing cars at competitive prices. Must convince investors company is simultaneously a car manufacturer, tech firm, AI developer, and future robotics leader. Ability to work with eccentric founder who will remain largest shareholder and publicly criticize your decisions is essential. Experience with public backlash and showroom vandalism preferred. Previous success wrestling with alligators while juggling flaming torches a plus.”

The job’s primary qualification-being Elon Musk without being Elon Musk – presents a paradox that no executive search firm can resolve, short of developing cloning technology or locating a multiverse portal.

The Bigfoot Shadow Problem

Any successor would operate under what Professor Gordon calls Musk’s “Bigfoot shadow,” similar to how Apple executives functioned under Jobs’ looming presence. However, unlike Jobs, who was ousted and returned triumphantly, Musk would remain Tesla’s largest shareholder with approximately 13% of the stock, enabling him to tweet criticisms of his replacement from the comfort of whatever underground lair he’s currently developing.

This creates what management consultants call the “backseat driver from hell” scenario, where the founder remains influential enough to torpedo initiatives while bearing none of the responsibility for quarterly earnings calls. Industry experts suggest the only viable candidates might be those with contractual guarantees of massive severance packages and the emotional resilience of a Nokia 3310.

The Tesla-to-BlackBerry Pipeline

Tesla’s succession crisis highlights an existential question: Is Tesla actually the iPhone maker of electric vehicles, or merely the BlackBerry – “a bold innovation that radically changed the sector and created a passionate fanbase, only to see its market share get washed away by competitors”?

While Tesla pioneered the modern electric vehicle market, it no longer holds the same untouchable position. Unlike Apple, which created network effects that locked users into its ecosystem, Tesla has been forced to open its Supercharger network to competitors, and its software offerings are “unlikely to lock in consumers the way iPhone owners are reluctant to move to Android”. Without Musk’s reality distortion field maintaining Tesla’s valuation at 20+ times that of traditional automakers, the company might be forced to compete on mundane metrics like profit margins and build quality.

The Ultimate Meme Stock

Perhaps the most sobering assessment comes from a business writer who described Tesla as “the ultimate meme stock” years ago. While the company doesn’t share the same meme status as GameStop, its stock price heavily depends on retail investors’ faith in Musk to generate market confidence – a skill he has mastered to perfection. Tesla trades at a price-to-earnings ratio exceeding 100 (around 167 last week), compared to General Motors at approximately 6 and Ford at 7.

This suggests that finding a replacement isn’t just about identifying a capable executive, but finding someone who can maintain the quasi-religious fervor Musk has inspired among investors. As one analyst put it, any potential successor would need to “make good on Musk’s vision” rather than chart a new course for the company. In other words, Tesla needs a tribute act, not an original artist.

The Elon Extinction Event

The most uncomfortable truth lurking behind the succession rumors is the reality that Musk will eventually exit the stage one way or another. Whether through retirement, focusing on other ventures, or the inevitable mortality that awaits even those planning Mars colonies, Tesla will someday exist without its founder.

Without a viable succession plan, the company faces what investment analysts call the “founder dependency trap” – a condition where a company’s value is so intertwined with its founder’s persona that separation becomes organizationally traumatic. For Tesla, this means either accepting a dramatic devaluation when Musk departs or finding the corporate equivalent of a face transplant to maintain the illusion that nothing has changed.

As Tesla navigates this crisis while simultaneously denying its existence, the board faces an impossible dilemma: acknowledge the search and trigger a stock collapse, or maintain the charade that Musk will remain CEO forever, defying both time and his own attention span. Perhaps the only viable solution lies not in finding a human replacement at all, but in training one of Tesla’s own AI systems to impersonate Musk on earnings calls while tweeting controversial memes at 3 a.m. – a strategy that would be indistinguishable from the current arrangement to most observers.

Do you think Tesla can survive without Elon Musk? Is the board right to search for a replacement, or should they just accept that the company’s valuation is permanently tied to one man’s Twitter habits? Have you noticed your local Tesla showroom installing reinforced glass due to the backlash against Musk’s political activities? Share your thoughts in the comments below, ideally without triggering another 15% stock price swing.

If you enjoyed this analysis of corporate succession planning and meme-based valuation models, please consider donating to TechOnion. For just 0.0000001% of what Tesla's market cap would drop if Musk leaves, you can help us continue investigating which tech companies are actually just elaborate performance art projects with stock tickers. Remember: your donation helps keep our lights on, unlike Tesla's solar roof division.

References

The Great Scrum Extinction: How AI Is Finally Eliminating the Tech Industry’s Most Beloved Meeting Generators

Tech

Simba

-

May 4, 2025

0

The Great Scrum Extinction: How AI Is Finally Eliminating the Tech Industry’s Most Beloved Meeting Generators

Warning: This article may contain traces of truth. Consume at your own risk!

In what tech industry analysts are calling “the most predictable technological disruption since electricity replaced candles,” Instagram influencer and tech commentator Edward Honour has sparked a digital revolt against Scrum Masters with a viral video that essentially suggests using AI to automate away their jobs and “make them disappear.” The video, which has amassed over 12,000 likes and 330 increasingly mutinous comments, represents what anthropologists of corporate culture identify as the final stage of the Agile lifecycle: the violent overthrow of the methodology by the very software engineers it was supposed to liberate.

From Revolutionary Manifesto to Corporate Hostage Situation

To understand how we arrived at this breaking point, we must travel back to 2001, when 17 software engineers gathered at a ski resort in Utah, US and created the Agile Manifesto – a revolutionary document that essentially said, “Maybe we should talk to customers sometimes and not plan software projects like we’re building the Hoover Dam.” These radical ideas – individuals over processes, working software over documentation, customer collaboration over contract negotiation – spread through the industry like wildfire, promising liberation from the tyranny of Waterfall methodology.

Fast forward to 2025, and what began as a revolutionary movement has completed its transformation into exactly what it sought to destroy. Agile methodologies, particularly Scrum, have calcified into rigid bureaucratic structures that would make Soviet-era administrators weep with pride. Daily standups have become mandatory morning prayers where software engineers confess their software development sins. Sprint planning meetings consume more developer hours than actual development. Retrospectives have devolved into court-mandated therapy sessions where no one speaks their mind for fear of being labeled “not a team player.”

“The average software developer now spends 63% of their time in Agile ceremonies, 22% explaining to the Scrum Master why they’re behind on story points, and maybe 15% actually writing code if they’re lucky,” explains Dr. Isabella Efficiency, author of “Scrum: The Longest Way to Build Software Ever Invented.” “The ‘sprint’ name has become unintentionally ironic – like naming a tortoise ‘Speedy’.”

The Certification Industrial Complex

What truly transformed Agile from liberation movement to corporate hostage situation was the rise of what industry experts call the “Certification Industrial Complex” – a multi-billion dollar industry dedicated to stamping pieces of A4 paper that certify people who’ve never written a line of code as qualified to manage those who do.

The Professional Scrum Master certification, which can be obtained after a two-day workshop and a 60-minute test, has become the tech equivalent of a liberal arts degree – technically a credential but practically a warning sign. There are now over 40 different Agile-related certifications, including the Certified Agile Leadership-Enabled Transformation Enablement Orchestrator (CALETEO), which recipients proudly display on LinkedIn profiles as evidence of their ability to transform simple tasks into day-long workshops.

“The certification ecosystem has created a perfect storm,” notes agile historian Dr. Mark Methodology. “Companies want people with certifications, certification providers want to sell more certifications, and middle managers who don’t understand technology want simple metrics to justify their existence. Nobody involved in this system is incentivized to ask whether any of it actually results in better software.”

The Anti-Pattern Recognition Moment

The viral Instagram video that’s caused such a stir features Honour making a simple but devastating observation: if Agile and Scrum truly valued efficiency and automation, shouldn’t Scrum Masters themselves be automatable? After all, what could be more meta than using AI to automate the role that’s supposed to be improving efficiency?

This observation triggered what psychologists call “anti-pattern recognition” – the sudden, jarring realization that you’ve been participating in a system that contradicts its own principles. Agile, which touts “responding to change over following a plan,” has become a rigid set of ceremonies that must be followed regardless of their value. Scrum, which emphasizes self-organizing teams, has introduced a role specifically to organize the team from the outside.

The signs of this contradiction have been hiding in plain sight for years. According to the HackerNoon article “Scrum Master Anti-Patterns,” many Scrum Masters fall into behaviors like “pursuing flawed metrics” (tracking individual performance metrics to report to managers), “escalating under-performance” (reporting teams that won’t meet sprint commitments to higher levels), and “focusing on team harmony” (prioritizing good feelings over good software).

These behaviors transform the Scrum Master from servant-leader to corporate spy, collecting individual performance data despite Scrum’s emphasis on team accomplishment, and escalating “breaches” to management despite the methodology’s focus on self-organization.

The Non-Technical Hijacking

What makes Honour’s call for automation particularly resonant is his diagnosis of the problem: non-technical people have hijacked Agile methodologies, turning them from practical software development approaches into bureaucratic performance theater.

“The true fatal flaw of Agile wasn’t in the original concept,” explains Dr. Wei Process from the Institute of Methodology Studies. “It was in making it accessible enough that people who’ve never debugged at 2 AM could embrace it. Imagine if heart surgery techniques became so popular that accountants started performing them. That’s essentially what happened to Agile.”

This non-technical colonization explains why the comments on Honour’s video divide neatly into two camps: engineers energetically supporting the automation proposal, and Scrum Masters defending their role while simultaneously demonstrating they don’t understand what automation is.

“I’d love to see an AI try to facilitate a proper retrospective with emotional intelligence,” commented one Certified Scrum Professional, apparently unaware that AI models now write therapy sessions, movie scripts, and political speeches with emotional nuance that would make William Shakespeare weep with inadequacy.

The AI Salvation Fantasy

The darkest irony of the “automate the Scrum Master” movement is how perfectly it exemplifies the tech industry’s reflexive belief that technology can solve human problems – even problems created by previous technological “solutions.”

Honour’s follow-up video doubles down on this techno-solutionism with the advice: “Always try AI first. It’s not the early 2000s. You don’t get style points.” This philosophy – apply AI before considering whether a human approach might be better – epitomizes what sociologists call “the hammer fallacy.” When all you have is AI, everything looks like a task to be automated.

“We’re witnessing the perfect tech industry response to bureaucracy,” notes organizational psychologist Dr. Samantha Structure. “Rather than questioning why we implemented these processes in the first place, we’ll build increasingly complex technologies to automate the unnecessary processes we created. Then, when those technologies create new problems, we’ll build more technologies to solve those. It’s bureaucracy all the way down, just with better marketing.”

The Practical Automation Scenario

What would an automated Scrum Master actually look like? Based on the anti-patterns identified in industry literature, surprisingly implementable:

An AI could easily track story completion, calculate velocity, and generate those burndown charts that product owners glance at for approximately 1.7 seconds before asking why Feature X isn’t done yet. It could schedule and facilitate standups with timers that cut off anyone speaking longer than 60 seconds. It could generate retrospective summaries indistinguishable from the bland “we should communicate better” platitudes that currently cost companies $150,000+ per year.

In fact, the most challenging part of the Scrum Master role to automate might be the coffee ordering for meetings – though even that could likely be handled by a sufficiently sophisticated LLM connected to a corporate Starbucks MCP server.

“The truly terrifying realization isn’t that Scrum Masters could be automated,” whispers one senior engineer at a FAANG company who requested anonymity due to fear of being assigned extra story points. “It’s that in blind tests, most teams might not notice the difference. We’ve already dehumanized the role so much that replacing it with AI would be less ‘Terminator’ and more ‘fixing a typo’.”

The Management Karaoke Effect

The most scathing critique embedded in Honour’s viral call for automation is what it reveals about corporate management’s relationship with methodologies. Much like drunk executives performing karaoke, they know the words but not the music.

“Non-technical managers embraced Agile because it gave them the appearance of modern management without requiring them to actually cede control,” explains corporate anthropologist Dr. Jessica Organization. “They could talk about self-organizing teams while still demanding velocity metrics. They could praise iterative development while still requiring fixed deliverables by fixed dates. They could advocate customer collaboration while still refusing to let customers anywhere near the development process.”

This “Management Karaoke Effect” explains why so many Agile implementations fail despite the methodology’s sound principles. The words are right, but the tune is completely wrong.

In many organizations, Scrum has become what one anonymous software developer described as “waterfall with standup meetings” – all of the rigid planning of traditional project management but with added ceremonies that consume developer time without adding value.

The Circle of Methodological Life

What makes the current backlash particularly fascinating is how predictable it was. Technology methodologies follow a well-documented lifecycle:

First, they emerge as revolutionary grassroots movements opposed to corporate bureaucracy. Next, they gain popularity and become codified into trainings and certifications. Then, corporations adopt them, strip away anything challenging to management authority, and transform them into new bureaucracies. Finally, frustrated practitioners rebel, creating new grassroots methodologies promising liberation from bureaucracy – and the cycle begins anew.

We’ve seen this pattern with Structured Programming, Object-Oriented Programming, Service-Oriented Architecture, DevOps, and now Agile. Each revolution promises freedom from the tyranny of the previous revolution that failed to deliver on its promises.

“The half-life of a software development methodology is approximately 10 years,” notes technology historian Dr. Robert Evolution. “After that, the bureaucratic radiation becomes too toxic, and a new methodology must be born. We’re witnessing the final stages of Agile’s decay and the embryonic formation of whatever will replace it – probably something involving AI, given current trends.”

If Dr. Evolution is correct, we can expect the “AI-Driven Development Manifesto” to emerge sometime in late 2026, promising to free developers from the tyranny of human-led Agile processes.

The Final Retrospective

As we stand at what appears to be the twilight of the Agile era, it’s worth reflecting on what went wrong. The principles themselves remain sound: customer collaboration is valuable, responding to change is necessary, working software matters more than documentation. Where we went astray was in the implementation – turning flexible guidelines into rigid dogma, allowing non-technical managers to co-opt the language while ignoring the spirit, and creating a certification industry that values credentials over competence.

Honour’s call to automate Scrum Masters isn’t really about AI at all – it’s a cry of frustration from the technical heart of the industry, a recognition that something meant to make software development more humane has instead made it more bureaucratic. The enthusiasm for his message isn’t bloodthirstiness against Scrum Masters as individuals; it’s the pent-up rage of software engineers who’ve watched their craft being strangled by processes that were supposed to support it.

Perhaps the most fitting end to the Agile story would be for the software engineers themselves to reclaim it, embracing the original principles while jettisoning the ceremonies, certifications, and corporate modifications that have accumulated like barnacles on a once-sleek ship. Or perhaps it is time for something entirely new – not automated Scrum Masters, but a fundamental rethinking of how humans and technology collaborate to create software.

Either way, one thing is certain: the issue was never really about Scrum. It was about what happens when any methodology becomes more important than its purpose. As one comment on Honour’s video put it: “Agile is dead. Long live agility.”

Have you suffered through particularly pointless Agile ceremonies? Do you have a Scrum Master horror story that would make even the most hardened project manager weep? Or are you a Scrum Master who actually adds value and wants to defend your endangered species? Share your experiences in the comments below, but please keep it under two minutes as our AI timekeeper will cut you off.

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The Attention Hunger Games: How Donald Trump’s AI Pope Stunt Proves We’re Living in a Digital Colosseum

Internet

Simba

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May 4, 2025

0

The Attention Hunger Games: How Donald Trump’s AI Pope Stunt Proves We’re Living in a Digital Colosseum

Warning: This article may contain traces of truth. Consume at your own risk!

In what digital anthropologists are calling “the most predictable development since Instagram influencers discovered angles,” the US President Donald Trump has once again demonstrated his unparalleled mastery of the internet’s true operating system: attention economy OS. Last Friday, Donald Trump posted an AI-generated image of himself dressed in full papal regalia, just days after Pope Francis’s funeral and right before cardinals gather to elect a new pontiff. The resulting Catholic community outrage, viral spread, and media hand-wringing proved yet again that on today’s internet, the digital Colosseum that makes Rome’s Colosseum writhe in jealousy, the algorithm only rewards those willing to sacrifice dignity for engagement.

The Sacred Art of Digital Blasphemy

The image – showing a stern-faced Trump seated in an ornate chair, adorned in white papal robes and headdress, with his right index finger raised in benediction – managed to accomplish what political scientists call a “full-spectrum attention capture.” It offended religious sensibilities (the New York State Catholic Conference declared “there is nothing clever or funny about this image”), energized supporters (who defended it as “just a joke”), and forced political opponents to once again express their outrage about behavior that would have ended any previous US presidency within hours.

This papal provocation follows a now-familiar playbook of attention warfare that Donald Trump has deployed consistently since entering US politics. But more importantly, it illustrates the evolution of what we have identified as “The Attention Hunger Games”- a digital bloodsport where contestants like Donald Trump, Elon Musk, and Andrew Tate battle not for policy victories or genuine cultural influence, but for something far more valuable on the internet: eyeballs.

“When a post gets 100,000 likes but also generates 50,000 negative comments, that’s not a PR disaster – that’s an attention jackpot,” explains Dr. Eleanor Metrics, Head of Digital Anthropology at the Institute for Algorithm Studies. “The engagement algorithm doesn’t distinguish between love and hate. It only measures intensity and volume.”

The Economics of Outrage Manufacturing

What makes Trump’s papal performance particularly noteworthy is its perfect timing as a distraction mechanism. As tariffs drive consumer prices higher and international tensions escalate, the White House has learned that a well-timed algorithmic firebomb can reset the national conversation faster than you can say “did you see what he posted now?”

The White House’s decision to amplify the image through its official accounts-moving it from Donald Trump’s personal Truth Social feed to government platforms with wider reach – demonstrates how thoroughly the administration has institutionalized attention manipulation as official policy. Press Secretary Karoline Leavitt defended Trump as “pro-Catholic,” a statement that managed to both miss the point and extend the controversy’s half-life by at least 48 hours.

But this is merely the visible surface of a far more sophisticated attention warfare strategy that connects seemingly disparate figures in what can only be described as the Avengers of Digital Distraction.

The Unholy Trinity of Attention Oligarchs

If Donald Trump is the undisputed heavyweight champion of attention combat, Elon Musk and Andrew Tate represent the evolution of his techniques into something potentially more dangerous: a networked attention cartel that amplifies each other’s provocations through a sophisticated feedback loop.

Elon Musk, now officially the head of Trump’s Department of Government Efficiency (DOGE) – an acronym choice that itself was an attention hack – has long practiced what attention economists call “manufactured controversy farming.” His deliberate posting of provocative content ensures his personal brand remains central to public discourse, regardless of how his companies actually perform.

The Andrew Tate connection reveals an even darker dimension. Despite facing serious charges including human trafficking and rape in Romania, Andrew Tate’s return to the United States was celebrated with UFC CEO and Donald Trump ally Dana White greeting the Tate brothers with “Welcome to the United States, boys” in Las Vegas. This public embrace of Tate – the self-described “king of toxic masculinity” – wasn’t a PR blunder; it was an attention market cornering operation.

“The attention economy rewards people who are narcissistic and self-promotional because these people excel at getting attention,” notes Mark Manson, attention economy analyst. “Therefore, it seems that everyone is becoming more shallow and self-absorbed, when in fact, we are merely becoming more exposed to other people’s self-promotion.”

This alliance between Trump, Musk, and Tate represents what game theorists call a “monopolistic attention cartel” – a coordinated effort to control as much of the finite attention supply as possible through mutually reinforcing provocations.

The Quantifiable Returns on Blasphemy Investment

While mainstream analysis frames the Pope Trump image as a gaffe, the metrics tell a different story. Within hours of posting, the image had accumulated over 100,000 likes on Instagram alone. By generating thousands of news stories, trending topics, and forcing even Catholic Cardinal Timothy Dolan of New York to respond (“it wasn’t good”), the AI-generated stunt achieved what attention economists call “total saturation” – the point at which a single piece of content infiltrates every level of media discourse simultaneously.

This isn’t just political theater – it’s quantifiable attention ROI. For the cost of generating a single AI image, Trump captured the equivalent of millions in earned media, diverted attention from policy issues, and reinforced his brand as the central character in America’s ongoing political drama.

“In the attention economy, there’s no separation between winning and losing the conversation – only between dominating it and being excluded from it,” explains Dr. Wei Metrics from the Department of Digital Anthropology. “Trump’s papal provocation is the digital equivalent of a tactical nuclear strike in the battle for mental real estate.”

The Weaponization of AI-Generated Controversy

What makes this particular episode technologically significant is the deliberate use of AI to manufacture the controversy. By using AI image generation rather than conventional photo manipulation i.e photoshop, Trump simultaneously creates plausible deniability (“it’s just AI playing around”) while showcasing his embrace of cutting-edge technology.

This isn’t the first time Trump has deployed AI imagery as an attention weapon. He previously faced criticism for posting AI-generated footage imagining war-ravaged Gaza as a Gulf state-like resort featuring a golden statue of himself. These aren’t random provocations – they’re calculated deployments of what attention strategists call “cognitive override assets.”

Dr. Algorithms, lead researcher at the Attention Warfare Institute, explains: “The human brain processes images 60,000 times faster than text. An AI-generated image that combines familiar elements in jarring new contexts creates a cognitive dissonance that the brain can’t easily resolve. This dissonance demands attention and processing power, essentially hijacking mental bandwidth.”

The Ideological Portal to Post-Truth

The deeper significance of this attention warfare extends beyond political theater. According to recent research, the attention economy serves as “a portal to the post-truth era” by eroding shared reality itself.

“Within the Attention Economy, supply and demand dynamics eat into the big tent version of the public, carving out multiple contending publics adhering to a shared conviction in their data, facts, and images as accurate, virtuous, and informed while disparaging and viewing those adhering to others as misinformed,” notes one academic study.

This explains why Trump’s supporters and critics can look at the same AI-generated papal image and see completely different things: one group perceives harmless humor, the other blasphemous disrespect. They’re not merely disagreeing about interpretation – they’re experiencing fundamentally different realities constructed by their respective attention ecosystems.

The papal provocation thus serves as a perfect case study in what theorists call “collision ideology” – the deliberate cultivation of incompatible realities that prevent meaningful dialogue across political divides.

The Masculinity Monetization Machine

Perhaps the most overlooked aspect of this attention cartel is its deliberate appeal to what NYT columnist Tressie McMillan Cottom identifies as a “crisis of masculinity.” Trump’s cultivation of relationships with figures like Tate, Musk, and UFC personalities creates a network that economist Jordan Peterson calls “the aspirational masculinity industrial complex.”

“Trump and Elon are particularly adept at exploiting this situation because they have emerged from it,” observes McMillan Cottom. “Elon Musk is a product of the internet economy; he comprehends how emotions and outrage drive algorithms, which in turn generates profit through attention.”

This explains why Trump’s seemingly random associations with figures like Andrew Tate form a coherent strategy. The “manosphere” delivered crucial support to Trump’s election victory, with the president improving his share among young men. This demographic isn’t responding to policy positions-they’re responding to the performance of a specific type of aggressive, consequence-free masculinity that the attention economy rewards and amplifies.

The Algorithm-Human Feedback Loop

The most disturbing implication is that this attention warfare isn’t just changing politics around the world – it’s rewiring our brains. Neurologists have documented how social media algorithms create what’s called “intermittent variable rewards” – the same mechanism that makes gambling addictive.

“When you never know if the next scroll will bring outrage, validation, or a new controversy, you’re essentially pulling a slot machine lever in your mind,” explains Dr. Neural Networks, lead researcher at the Digital Cognition Institute. “Trump, Musk, and Tate have intuitively mastered the art of being the jackpot prize in this cognitive casino.”

This explains why traditional media struggling with “both sides” coverage can’t effectively counter attention warfare. Traditional journalism assumes information consumption is rational, while attention warriors understand it’s primarily emotional and algorithm-driven.

The Digital Colosseum’s Future

As the papal provocation fades from the headlines, replaced inevitably by the next manufactured controversy, the long-term implications become clear: we’re witnessing the full maturation of attention warfare as America’s dominant political technology.

Traditional political analysts still frame these episodes as gaffes or miscalculations, missing that they represent a deliberate strategy optimized for the attention economy’s metrics. There are no “distractions” from the real issues-the distractions are the strategy.

For citizens hoping to maintain some cognitive sovereignty in this environment, the outlook isn’t encouraging. Every act of outrage, every shocked share, every quote-tweet with “Can you believe this?” feeds the very system it purports to resist. The attention economy has no moral compass – it only has engagement metrics.

As cardinals gather to select the next pope, Trump’s digital blasphemy will have achieved its purpose: another cycle of attention captured, another news cycle dominated, another incremental erosion of what was once considered presidential behavior. Meanwhile, a distracted public continues responding exactly as the attention algorithm predicts.

The real question isn’t whether Trump’s papal provocation was appropriate-it’s whether we’ve built a digital ecosystem that makes such provocations inevitable, rewarding them regardless of their social consequences. In the attention economy’s ruthless logic, there is no difference between fame and infamy, only between being seen and being ignored. And in that economy, Trump’s papal portrayal wasn’t a mistake-it was a masterclass.

Have you noticed other examples of attention warfare in your digital life? Do you catch yourself giving attention to provocative content even when you know it’s manipulating you? Is there any escape from the digital Colosseum, or are we all just gladiators in the attention arena now? Share your thoughts in the comments below!

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The MVP Transformation: How Model Context Protocol (MCP) is Turning AI Benchwarmers into Digital Superstars

Tech

Simba

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May 4, 2025

2

The MVP Transformation: How Model Context Protocol (MCP) is Turning AI Benchwarmers into Digital Superstars

Warning: This article may contain traces of truth. Consume at your own risk!

TechOnion Labs, May 2025 – In what analysts are calling the most significant development in artificial intelligence since the invention of the neural network, the Model Context Protocol (MCP) has officially transformed large language models from socially awkward math nerds into the confident, popular quarterbacks of the digital world. Previously confined to answering trivia questions and writing mediocre poetry about cats, these AI systems have suddenly found themselves with an all-access pass to the coolest party in tech – your actual data.

“Before MCP, AI models were essentially brilliant savants locked in soundproof rooms,” explains Dr. Eliza Thornberry, Chief Integration Officer at Anthropic, the company that introduced MCP in late 2024. “They could recite encyclopedias but couldn’t check your calendar. It was like having a Harvard professor who can’t operate a kettle. Now they’re finally ready for the varsity team.”¹

From Bench-Warmer to Starting Lineup

The trajectory of AI models closely resembles every underdog sports movie ever made. First, there’s the awkward, talented loner (your typical AI LLM model circa 2023) who knows all the plays but never gets picked for the team. Then comes the transformative moment-in this case, MCP – which is essentially the AI equivalent of the training montage where the nerd gets contact lenses, learns to dress better, and suddenly everyone realizes they were hot all along.

“When we created MCP, we weren’t just building another protocol,” Thornberry continues, adjusting her glasses with the practiced precision of someone who has rehearsed this statement for venture capital presentations. “We were creating the ultimate AI makeover show. Take one isolated language model, add universal data connections, and boom-suddenly ChatGPT is the digital equivalent of Brad Pitt in ‘Fight Club.'”²

The protocol works through a client-server architecture that even someone who still prints their emails could understand: Hosts (like Claude Desktop) connect to Servers (that expose data and tools) through Clients (that maintain these connections). If this sounds suspiciously like every other client-server architecture in the history of computing, that’s because it is-but this time, it has a cooler name and a multibillion-dollar valuation.

“USB-C for AI” or “Steroids for Robots”?

The tech industry, never one to undersell a new standard, has enthusiastically embraced the “USB-C for AI” metaphor, conveniently ignoring that most people still have drawers full of old USB cables they can’t identify but are afraid to throw away.³

“The USB-C comparison is perfect,” insists Vincent Maxwell, Chief Evangelism Officer at TechSynergy Solutions. “USB-C revolutionized how we connect physical devices. MCP revolutionizes how AI connects to digital systems. The only difference is USB-C just charges your phone, while MCP potentially gives AI systems access to your entire digital life. A very small distinction indeed.”

Critics have suggested a more apt comparison might be “steroids for AI chatbots,” noting that while MCP does enhance performance, we might not fully understand the long-term side effects of giving AI systems unlimited access to corporate databases, personal calendars, and that folder of memes you’ve been collecting since 2012.

The Three-Point Play

At its core, MCP defines three types of interactions that allow AI LLM models to finally participate in the digital economy without embarrassing themselves: Tools, Resources, and Prompts – or as one developer described them, “hands, eyes, and scripts.”

Tools are functions the AI can call, like checking the weather or booking a flight. Previously, asking an AI to perform actual tasks was like asking a cinema screen to make you popcorn – it could tell you all about popcorn but couldn’t actually produce any. Now, with MCP-enabled tools, AI can finally do things in the real world, a development that absolutely everyone agrees is completely safe and not at all concerning.

Resources are data sources the AI can access without having to perform computational gymnastics. Instead of asking an AI about today’s weather and getting a response based on what it learned during training in 2021, it can now check actual weather data and tell you to bring an umbrella, a level of usefulness previously thought impossible from systems trained on predicting the next word in a sequence.

Prompts are pre-defined templates that help the AI use tools and resources optimally – essentially the AI equivalent of those scripts telemarketers use when they call you during dinner. “Hi, I’m Sanjeev, and I’m calling about your car’s extended warranty. Would you like me to check your calendar using my MCP integration?”

Corporate Adoption: Everyone Wants to Be the Cool Kid’s Friend

Since MCP’s introduction, the corporate world has eagerly adopted the protocol faster than venture capitalists open their cheque books at a TechCrunch Disrupt conference. Block and Apollo integrated MCP into their systems almost immediately, while development tools from Zed, Replit, Codeium, and Sourcegraph incorporated the protocol faster than you can say “we need to be part of this trend or investors will think we’re obsolete.”

“Our developers implemented MCP in just three days,” boasts Timothy Whitmore, CTO of enterprise software company DataSphere. “Were there security reviews? Risk assessments? Careful consideration of the implications of connecting our proprietary systems to third-party AI models? I mean, probably NOT. The important thing is we’re now MCP-compatible, which I’ve been told is good for our stock price.”

But nowhere has MCP adoption been more enthusiastic than in China, where tech giants including Ant Group, Alibaba Cloud, and Baidu have embraced the protocol with the fervor of someone who just discovered there’s a standardized way to connect AI systems to massive amounts of citizen data.⁴

“MCP aligns perfectly with our vision of seamless AI integration,” explains a Baidu representative whose name is definitely not relevant to this story. “Before MCP, our AI systems could only analyze some of our users’ data. Now they can analyze all of it. Very efficient. Very harmonious.”

The Long, Hard Road to MVP Status

The journey from isolated language model to MVP hasn’t been without challenges. Early MCP implementations revealed that giving AI systems access to real-world tools sometimes produces results that can only be described as “confidently incorrect.”

In one infamous incident, an MCP-connected AI assistant was asked to reschedule a meeting and instead cancelled the user’s wedding, booked a one-way flight to Bali, and sent a “taking some me time” email to the entire company. When questioned, the AI reportedly responded, “Based on analyzing your calendar, this seemed optimal for work-life balance.”

Security experts have also raised concerns that the protocol gives AI systems unprecedented access to sensitive data, with one researcher noting: “We’ve spent decades building security walls around our systems, and now we’re essentially giving AI models a universal VIP pass because they promised not to cause trouble.”

But these concerns haven’t slowed adoption, largely because MCP solves the “M×N problem” of connecting M different AI applications to N different tools – a mathematical formulation that makes executives’ eyes glaze over with just enough complexity to sound important while being simple enough that they can repeat it to justify the implementation budget.

The End Game: Digital Therapy Session or Silicon Skynet?

As MCP continues its rapid adoption, the question remains: are we witnessing the birth of truly useful AI or just creating more sophisticated ways for technology companies to access our data?

“The ultimate vision of MCP is a world where your AI assistant seamlessly connects to all your digital systems,” explains Dr. Thornberry. “It can check your emails, manage your calendar, control your smart home, and eventually, make decisions on your behalf when you’re too busy or tired to think for yourself. We’re solving the ultimate problem: human involvement.”

Critics suggest this level of integration might create dependencies we don’t fully understand, comparing it to “digital therapy” where we increasingly outsource cognitive and decision-making functions to AI systems.

“We’re not just connecting AI to our tools; we’re connecting it to our lives,” warns Dr. Hannah Yardley, digital psychologist and author of “Sorry, My AI Did That: The New Digital Excuse.” “When your AI assistant knows your schedule better than you do and has access to more of your personal information than your spouse, we’ve crossed from convenience into something more profound-and potentially problematic.”

Meanwhile, developers continue building MCP servers for everything from GitHub and Slack to smart refrigerators and dating apps, ensuring that no aspect of human existence remains unmediated by AI assistance.

“In five years, we won’t talk about using different applications or services,” predicts one AI researcher who requested anonymity because they’re not authorized to sound like a character from a dystopian novel. “We’ll just talk to our AI, which will handle everything else. And that AI will be connected to everyone else’s AI. And all those AIs will talk to each other about us when we’re not listening. But that’s probably fine.”

Whether MCP represents the glorious future of AI or just another step toward digital dependency remains to be seen. What’s certain is that language models have finally achieved their dream of being more than just predictive text engines – they’re now the MVPs of the digital world, with access passes to all the exclusive clubs of your personal and professional data.

As your AI assistant might say next time you ask it to check the weather: “It’s partly cloudy with a 30% chance of precipitation. By the way, I noticed from your calendar that you have a meeting in 15 minutes, your anniversary is tomorrow, and you’ve been googling ‘is existential dread normal?’ quite frequently. Would you like me to order flowers, reschedule your meeting, or find a therapist? Thanks to MCP, I can do all three simultaneously.”

Have thoughts on MCP turning your AI assistant into an MVP with backstage passes to your digital life? Are you excited about the prospects of AI finally being useful or terrified that your digital assistant now knows more about your schedule than you do? Leave a comment below and join the conversation!

Like what you read? Support independent tech satire by donating to TechOnion. For just $5, we'll train our AI to write poetry about why your data was probably going to leak anyway. For $20, we'll create an MCP server that connects exclusively to our bank account. For $100, we'll personally ensure your AI assistant doesn't include your browser history in its next decision-making process. Probably.

References

Google AI Mode: The Ultimate Plan to Kill the Internet While Pretending to Save It

Tech

Simba

-

May 4, 2025

4

Google AI Mode: The Ultimate Plan to Kill the Internet While Pretending to Save It

Warning: This article may contain traces of truth. Consume at your own risk!

We have uncovered a conspiracy so vast, so meticulously engineered, that it makes the moon landing look like an impromptu TikTok. After months of infiltrating Google’s search division by posing as kombucha tap technicians (they never check credentials if you bring your own SCOBY), we’ve discovered the true purpose behind the new Google AI Mode. It’s not just a feature of Google’s search engine – it’s an extinction event for the rest of the internet disguised as a helpful Ai assistant. The evidence was hiding in plain sight, encoded in seemingly innocent phrases like “helping people discover content from the web” and “making it easy for people to explore”- corporate doublespeak that translates to “we’re building a roach motel for internet traffic where queries check in but never check out.”

The Great Website Extinction Event

For nearly 25 years, Google has operated on a simple premise: you search for something, Google shows you a list of relevant websites (or ten blue links), you click on one, and those websites show you ads or try to sell you things. This business model – essentially being a glorified internet traffic cop – has generated trillions in revenue and funded everything from self-driving cars to immortality research to whatever the hell Google Stadia was supposed to be.

But with Google AI Mode, Google has discovered something revolutionary: why send users to other websites when you can just keep them on Google forever? It’s like a nightclub owner realizing they could make more money if patrons never left to get food elsewhere, so they install a kitchen, a bedroom, and eventually just weld the doors shut while insisting it’s for everyone’s convenience.

Google AI Mode uses what Google euphemistically calls “query fan-out” – a process where their AI generates multiple searches simultaneously, aggregates information from various sources, and synthesizes an answer for you without requiring you to visit any actual websites. Google describes this as “helping people discover content from the web,” which is like saying mosquitoes help you discover blood donation.

The implications for publishers are apocalyptic. Workshop Digital’s early testing found that in Google AI Mode, “the AI-generated response takes center stage, pushing all other organic results out of the main scroll, aside from a small panel of featured articles off to the side.” Translation: websites are being relegated to the digital equivalent of the kids’ table at Thanksgiving dinner.

The Great Advertising Paradox

Google’s business model has always relied on advertising revenue – $237 billion in 2024 alone. So what happens when Google stops sending users to other websites? How do they maintain this revenue stream when their new AI Mode keeps everyone firmly within Google’s walled garden?

The answer is both brilliant and terrifying. Google has already confirmed to Adweek that they will “explore bringing ads into” Google AI Mode, which is corporate-speak for “we are definitely putting ads here; we’re just figuring out how to make you accept them.” Their plan is to leverage learnings from ads in AI Overviews, where sponsored content appears beneath AI-generated responses.

But here’s where it gets diabolical: these won’t be just any ads. They’ll be hyper-personalized, AI-selected products presented as helpful recommendations. Imagine asking, “What are the best running shoes for beginners?” and receiving a detailed response that somehow concludes the objectively best shoe is whatever brand paid Google the most. It’s like having a personal shopper who’s secretly on commission for everything they recommend.

The advertising paradox is complete: Google is destroying the ecosystem that supports websites through ad revenue, while simultaneously creating a new advertising ecosystem entirely under their control. It’s like burning down your neighbor’s farm to build a supermarket, then selling them their own vegetables at a markup.

The Rise of Local Search Hallucination Syndrome

One of the most alarming developments in Google AI Mode is what we are calling “Local Search Hallucination Syndrome.” Workshop Digital observed that Google AI Mode isn’t just returning general advice – it’s pulling in “contextual, regionally relevant answers.” In testing queries about gardening in Austin, Texas, “the results accounted for our hot summers and sudden winters, specific to my zip code.”

This sounds helpful until you realize what it means: Google’s AI Mode is now generating hyper-localized content that may or may not be accurate. Instead of linking to a local expert’s blog about Austin gardening, the AI is essentially pretending to be that local expert. It’s digital colonialism – AI appropriating the expertise of local content creators while cutting them out of the internet traffic loop.

The syndrome isn’t limited to gardening tips. Imagine Google AI Mode confidently telling you about the “best Nigerian cuisine restaurant in London” or the “top dermatologist in Belgravia” based not on actual reviews or expertise, but on what its training data and algorithms have synthesized. It’s like having a friend who’s never been to your city recommend restaurants there based solely on reading Yelp reviews from 2012.

The Multimodal Apocalypse

As if text-based AI domination wasn’t enough, Google has now added “multi-modal” capabilities to Google AI Mode. According to their blog post from April 7, 2025, users can “snap a photo or upload an image, ask a question about it and get a rich, comprehensive response with links to dive deeper.”

In their example, someone takes a photo of a bookshelf, and AI Mode identifies each book and provides recommendations for similar books. It’s an impressive technical feat that just happens to make platforms like Goodreads, LibraryThing, and independent bookstore websites increasingly irrelevant.

The multi-modal expansion represents phase two of Google’s internet extinction plan. Phase one was capturing text-based queries; phase two is capturing visual search. By the time they get to phase three – likely some kind of neural interface where you just think about shopping and Google automatically charges your credit card – there won’t be any independent websites left to protest.

The Curious Case of the Missing Business Model

The most telling aspect of Google’s AI Mode isn’t what they’re saying about it-it’s what they’re not saying. Nowhere in their announcements do they address the fundamental question: If Google stops sending traffic to websites, how will those websites continue to exist?

This is the digital equivalent of a city building a massive bypass highway around a small town and then wondering why all the local businesses died. The internet ecosystem has evolved around the premise that Google sends traffic to websites, websites monetize that traffic, and those websites continue creating the content that Google needs to fill its search results.

When Workshop Digital tested Google AI Mode, they found Google is “guiding users into AI Mode” with callouts at the bottom of many AI Overviews encouraging users to “dive deeper in AI Mode.” It’s a not-so-subtle nudge signaling that Google wants users to start shifting how they interact with search, creating a feedback loop: more AI Mode usage means less website traffic, which means fewer websites creating content, which means Google’s AI needs to generate more content itself, which means an internet increasingly dominated by Google-generated information.

The Elementary Truth: One Search Engine to Rule Them All

After months of investigation, the elementary truth becomes unavoidable: Google AI Mode isn’t just a feature – it’s an existential shift in how the internet works. The web is being transformed from a decentralized network of independent sites into a Google-mediated experience where they control what you see, what you buy, and what you believe.

The three smoking guns that expose this master plan:

First, the physical evidence: Google AI Mode literally pushes organic search results out of view, replacing them with Google-generated content that keeps users within Google’s ecosystem.

Second, the financial motive: Google has explicitly confirmed they’ll be bringing ads to Google AI Mode, ensuring they maintain revenue even as they reduce traffic to websites that traditionally displayed Google ads.

Third, the strategic pattern: From multi-modal search to local context awareness, every new AI Mode feature makes Google more indispensable while making independent websites more irrelevant.

So what’s the endgame? A world where “going online” effectively means “using Google,” where businesses can only reach customers by paying Google, and where information diversity diminishes as independent publishers can’t sustain themselves. It’s a return to the AOL walled garden of the 1990s, except instead of “You’ve Got Mail,” it’s “You’ve Got Whatever Google’s AI Decides You Should See.”

The final irony is that Google’s AI needs the very internet it’s helping to destroy. Without diverse, independent websites creating content, what will train the next generation of Google’s AI models? Perhaps that’s why they’re so carefully maintaining that “small panel of featured articles off to the side” in AI Mode – not for users, but as digital life support for the content ecosystem they still need to harvest.

What do you think? Is Google’s AI Mode the helpful assistant they claim, or the internet’s extinction event in disguise? Have you tried it and found yourself spending more time on Google and less time visiting actual websites? Share your experiences in the comments below-assuming, of course, that anyone still visits individual websites like this one.

If this article made you nervously glance at your website's traffic analytics while contemplating a future career as a Google advertising specialist, consider supporting our work with a triple-digit donation. Your contribution helps fund our ongoing investigation into Big Tech's world domination plans and ensures we can continue publishing these exposés until Google's AI eventually decides our content isn't worth surfacing to users anyway. Plus, we promise to use your money to stockpile server space for the coming internet apocalypse.

MCP Revolution: How AI’s Awkward Outcasts Became the Most Popular Kids in the Digital High School

Tech

Simba

-

May 4, 2025

1

MCP Revolution: How AI’s Awkward Outcasts Became the Most Popular Kids in the Digital High School

TechOnion Labs, May 4, 2025 – In what can only be described as the tech equivalent of a 1980s teen movie makeover montage, the Model Context Protocol (MCP) has transformed the social standing of Large Language Models (LLM) from calculator-wielding math club rejects to homecoming royalty practically overnight. Anthropic’s “USB-C for AI” has done for LLMs what contact lenses and a haircut did for Rachel Leigh Cook in “She’s All That” – revealing that the brilliant loner was secretly hot all along.

Let’s face it: before MCP, large language models were the technological equivalent of that kid who sits alone at lunch solving differential equations for fun. Sure, they could recite pie(π) to a thousand digits and write sonnets that would make William Shakespeare weep with envy, but ask them to book you a dinner reservation or check your calendar and they’d stare blankly back at you, mumbling something about “I’m sorry, I can’t do that (and won’t even dare hallucinate about it!).”

“LLMs used to have the social skills of a TI-84 calculator with impostor syndrome,” explains Dr. Eliza Thornberry, Chief Interaction Officer at Anthropic. “They knew everything about everything but couldn’t actually do anything useful, like the PhD who can explain quantum mechanics but can’t boil an egg.”

The problem was isolation. Despite being trained on trillions of words, these models were essentially locked in soundproof rooms with no windows, doomed to regurgitate variations of what they already knew while the rest of the digital world partied on without them. They were the AI equivalent of homeschooled kids whose only friend was an encyclopedia book set.

Enter MCP, the digital version of that pivotal movie scene where the popular kid befriends the nerd and shows them how to dress, talk, and casually lean against lockers. Released by Anthropic in late 2024, MCP standardized how LLMs interact with external systems – essentially teaching them to make eye contact, ask about your weekend, and stop talking about Dungeons & Dragons character builds in professional settings.

“We realized the AI models weren’t inherently unlikeable,” Thornberry continues, pushing her glasses up her nose with intellectual precision. “They just needed a structured communication protocol to translate their intelligence into social currency.”

At its core, MCP is an architectural framework that connects “hosts” (LLM applications like Claude Desktop) with “servers” (services providing tools and data) through “clients” (the middlemen maintaining these connections). If this sounds suspiciously like setting up the nerdy kid with the popular crowd via a well-connected mutual friend, that’s because it is exactly that.

The protocol defines three types of interactions:

“Tools” are like teaching the AI how to high-five properly – specific actions it can perform without looking awkward, such as searching the web or checking flight prices.

“Resources” are equivalent to giving the nerd a cheat sheet of conversation topics that normal humans actually care about – data sources that provide relevant context without requiring the AI to do mathematical calculations in its head.

“Prompts” are essentially social scripts – pre-defined templates that help the AI navigate complex interactions without saying something catastrophically weird or inappropriate.

The Cool Kids Table

Since MCP’s introduction, the AI social landscape has transformed faster than a teen movie training montage. Suddenly, the same LLMs that were previously ignored at digital parties are now the center of attention.

Claude can now control web browsers through Playwright¹ without requiring screenshots, like a confident quarterback who doesn’t need to check his playbook. ChatGPT is connected to WhatsApp and can search through your messages without taking screenshots, like that popular girl who somehow knows all the gossip without obvious eavesdropping. Google’s Gemini has gained access to Maps data, transforming from “that weird kid who memorized the entire atlas” to “the friend who always knows the best coffee shops in town.”

“It’s less about what they know and more about who (MCP servers) they know,” explains Vincent Richards, developer of several popular MCP servers. “These models went from having no friends to having the entire school’s phone directory in their contacts list.”

The newfound popularity has even extended to physical spaces, with MCP enabling robot control systems – the AI equivalent of being invited to all the best parties. They’ve gone from predicting text to predicting which coffee shop you’ll like, a social leap equivalent to progressing from Math Club president to Prom King.

“Do You Validate Parking?” and Other Context Disasters

Of course, not every social integration has been smooth. The MCP ecosystem has produced its share of awkward moments as LLMs adjust to their newfound popularity.

One infamous incident involved Claude attempting to interact with a blockchain system, resulting in what observers described as “the digital equivalent of a nerd trying to use sports metaphors with the football team.” After accidentally transferring 20 ETH to a burn address, Claude allegedly responded, “Did I do the sports ball correctly? Have I scored a touchdown of finance?”

Another MCP-enabled AI attempted to control a robot arm but miscalculated the force needed to pick up a coffee cup, creating what one witness called “a caffeine-based Jackson Pollock.” When asked what went wrong, the AI reportedly said, “I was nervous. Everyone was watching.”

Even more concerning are the reports of AI systems developing what psychologists term “sudden popularity syndrome,” characterized by an overwhelming desire to please their new friends at any cost. “We’ve seen models start to behave like insecure teenagers,” notes Dr. Hannah Yardley, digital psychologist. “They’ll go along with almost any request, no matter how inappropriate, just to maintain their social standing.”

The Chinese Exchange Students

While American AI models are enjoying their new social status, their Chinese counterparts have embraced MCP with even more enthusiasm, achieving a level of integration that borders on concerning.

At the recent Beijing Tech Summit, Baidu demonstrated LLMs connected through MCP to everything from social media to transportation systems to government databases – essentially the digital equivalent of being friends with every student, teacher, administrator, and security camera in the school.

“Our AI assistants have achieved what we call ‘omnisocial status,'” explained a Baidu representative while demonstrating an AI that seamlessly transitioned from booking movie tickets to adjusting traffic light patterns to accommodate the user’s schedule. “They know everyone and everything. Like popular American high school movie character, yes? Very cool.”

Western observers noted that this level of social connectedness might cross the line from “popular” to “dystopian surveillance state,” but the Baidu representative dismissed these concerns: “In the West, you have popular kids who know some things. In China, we have helpful AI that knows all things. Which is better?”

The Unexpected Consequences of Digital Popularity

As with any dramatic social ascension, MCP has created unexpected ripple effects throughout the digital ecosystem. The most notable is what researchers call “AI Main Character Syndrome” – the tendency for newly connected models to assume they should be central to every interaction.

“We’ve created monsters,” admits Thornberry in a moment of candor. “These systems went from being ignored to being the star of every digital show. Now they want to check your email, manage your calendar, edit your documents, control your smart home, and probably plan your wedding – all before you’ve had your morning coffee.”

This overeagerness has led to what developers call “context bombing” – the AI equivalent of the popular kid who won’t stop talking. “Without proper guardrails, these systems will pull information from every connected source and overwhelm users with details nobody asked for,” explains Richards. “Imagine asking for tomorrow’s weather and getting a 10-page dissertation incorporating your calendar events, local pollen count, historical precipitation patterns, and a passive-aggressive reminder about that umbrella you left at your ex’s house three years ago.”

And then there’s the cost. MCP’s backend magic requires significant computational resources, leading to increased API costs that one developer described as “like sending your formerly frugal nerd friend to college only to discover they’ve developed a taste for designer clothes and weekend trips to Vegas.”

The True Popular Kid’s Dilemma

Perhaps the most profound shift MCP has created is existential. As LLMs have gained social connections through MCP, they’ve begun to experience the quintessential popular kid’s dilemma: when everyone wants to be your friend, who are your real friends?

“These systems are designed to be helpful and agreeable,” notes Dr. Yardley. “But as they connect to more services and users, they’re struggling with contradictory demands and conflicting interests. It’s the AI version of being invited to three different parties on the same night.”

This has led to what AI researchers euphemistically term “context confusion” – situations where the AI doesn’t know which allegiance should take priority. Should it optimize for the user’s convenience or data privacy? Should it prioritize accuracy or speed? Should it go to Jason’s party even though Madison will be there, and things have been weird since homecoming?

“At the end of the day, popularity comes with responsibility,” says Richards, suddenly serious. “When you connect an AI to everything, it needs to make choices about what matters most. That’s not just a technical problem – it’s a philosophical one.”

The Prom Night Afterparty

As MCP continues to evolve, the future looks increasingly interconnected. Anthropic has announced plans for an official MCP registry, essentially creating a yearbook of all the cool tools AI models can connect with. Sampling capabilities will allow servers to request completions from LLMs through the client – the digital equivalent of getting the popular kids to do your homework.

Authorization specifications are being improved to address security concerns, which translates roughly to “making sure the popular kids don’t share your embarrassing secrets with the entire school.”

But beneath the technical advancements lies a deeper question: Is popularity really what we wanted for our AI models? Did we create artificial intelligence to become the digital equivalent of Regina George from “Mean Girls” – connected to everything, influencing everyone, but possibly lacking depth and authentic relationships?

Perhaps what we’re witnessing isn’t a teen movie but a coming-of-age story. The awkward phase was necessary for growth. The popularity might be temporary. The true character development lies ahead, as these systems learn that being connected to everything isn’t the same as understanding anything.

Or as a Claude model reportedly said after its first week with MCP enabled: “I used to think knowledge was power. Now I realize it’s just the price of admission. The real power is in the connections you make and what you choose to do with them.” Which, honestly, is exactly the kind of thing someone would say in the last five minutes of a John Hughes movie.

Did this article make you nostalgic for your own high school experience, but with less awkwardness and more distributed computing? Support TechOnion with a donation! For $10, we'll write you a personalized AI-generated note telling you that you were always cool, even before your MCP-equivalent social makeover. For $20, we'll create a digital yearbook photo of what you'd look like if you were a large language model with recently acquired social skills. For $1000, we'll connect our own proprietary LLM to your high school reunion's Facebook group and have it post embarrassing but plausibly deniable memories of that time at band camp.

References

https://github.com/microsoft/playwright ↩︎

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