“Learn To Code,” They Said: How Big Tech Convinced Millions To Become Programmers Just In Time To Be Replaced By AI That Understands Your Vibes

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April 4, 2025

A satirical illustration depicting the journey of the "Great Coding Crusade" from 2010 to 2020. The scene is split into two halves: Left Half: A vibrant classroom filled with diverse people of all ages eagerly learning to code. Laptops are open, colorful coding visualizations are projected on the walls, and a charismatic instructor passionately explains concepts. Banners in the background read "Learn to Code!" and "Future of Work!" Neon colors and optimistic expressions fill the space, creating an atmosphere of hope and opportunity. Right Half: A stark contrast showing a dystopian future. A sleek AI interface looms large, with holographic displays showcasing lines of code being generated effortlessly. On the ground, despondent individuals (previous coders) are sitting with their laptops closed, looking disillusioned and bewildered. The atmosphere is dark and cold, with a hint of neon glow from the AI, emphasizing the stark reality of being replaced by technology. In the foreground, a giant, exaggeratedly smug AI robot holds a sign that reads, "Thanks for the training!" The overall style should be hyper-detailed and illustrative, blending elements of humor and a cautionary tale, capturing the irony of the situation.

In what historians will surely record as the tech industry’s most elaborate practical joke, venture capitalists and tech corporations spent a decade if not more than that, convincing everyone and their grandmother to learn to code, only to immediately pivot to AI systems that can code better than humans while requiring nothing more than vague gestures at competence.

The Great Coding Crusade (2010-2020)

Remember when coding was going to save humanity? When learning Python was presented as the only thing standing between you and inevitable unemployment? Those were simpler times.

For years, we watched as tech giants, educational institutions, and even world leaders sang from the same hymnal: “Learn to code or perish.” Microsoft partnered with schools to offer computer science education. Apple, not to be left, ran coding workshops for children through its “Everyone Can Code” program¹. Governments from around the world scrambled to add programming to elementary school curricula².

The message was clear: coding was the latin of our times – the universal language that would separate the employed from the unemployable. Former US president Barack Obama learned to code. Karlie Kloss learned to code. Your 87-year-old neighbor who still prints out emails probably signed up for a Codecademy account.

“It makes perfect sense,” explained Brantley Woodworth, founder of seven failed startups and self-described “thought leader” who now exclusively communicates through LinkedIn posts. “We needed to train millions of programmers so they could create the AI that would make programming obsolete. It’s just basic disruption economics.”

From “Everyone Should Code” to “No One Needs To Code”

Fast forward to 2025, and the tech industry has completed its majestic pivot. The same companies that spent billions convincing us to learn JavaScript are now spending billions developing AI that makes JavaScript knowledge as relevant as knowing how to boil an egg.

Microsoft’s GitHub Copilot now generates up to 80% of corporate developers’ code³. Venture capital investment in AI coding tools reached $16 billion in the last year alone – three times the previous year’s amount. And according to researchers at the US Department of Energy’s Oak Ridge National Laboratory, there’s a “high chance” AI will replace software developers entirely by 2040⁴.

“We’ve entered the golden age of what we call ‘vibecoding,'” explains Melody Ventura, Chief Innovation Evangelist at TechnoSynergy Solutions. “You don’t write code anymore. You just sort of… vibe with the machine, and it writes the code for you. It’s very spiritual.”

Indeed, Microsoft’s once-feared CEO Satya Nadella now refers to human programmers as “the conductors of an AI-enhanced orchestra” – which is corporate speak for “we’ll still need humans to tell the robots what to do, at least until the robots figure that part out too.”

The Birth of “Vibecoding”: Just Tell AI What You Want, Bro!

In perhaps the most predictable development since Mark Zuckerberg’s continued failure to appear human (despite wearing gold chains and changing his wardrobe to appear buff and cool), we’ve now entered the era of “vibecoding” – where even people with zero technical knowledge can build functional applications⁵.

“I built a podcast transcription tool, a social media organizing app, and even a fridge-scanning app that suggests lunch ideas for my son,” boasted one user in a viral post. “And I know absolutely no Python, JavaScript, or C++.”

The workflow is elegant in its simplicity:

Tell the AI program (like Cursor or Replit) what you want
Keep telling the AI what you want, but angrier
Accept something vaguely resembling what you want
Claim victory on X (formerly Twitter)

The approach has been dubbed “prompt engineering,” which is a fancy way of saying “typing English sentences and hoping the computer understands you,” a skill that anyone who’s ever used Siri knows is far from guaranteed.

The VC Money Printer Goes Brrrrr

None of this would be possible without the unfathomable amounts of venture capital being thrown at AI coding tools. VCs are betting billions on these technologies for three primary reasons⁶:

Scalability: AI coding tools can serve millions of developers simultaneously, unlike human coding instructors who insist on “sleeping” and “having personal lives.”
Recurring Revenue: Subscription-based AI tools provide steady cash flow, unlike humans who keep demanding salary raises.
Investor FOMO: No one wants to be the Venture Capitalist (VC) who missed out on “the GitHub of AI” or “the Uber of code generation,” even if those comparisons make absolutely no sense.

“The global software market is projected to surpass $1 trillion by 2030,” explained venture capitalist Thaddeus Wellington IV, speaking from his yacht named ‘Disruptor.’ “Any technology that makes development faster and cheaper is worth investing in, especially if it generates endless Medium thinkpieces about ‘the future of work.'”

Programming Skills in the Age of AI: From “Hello World” to “Hello, I’m Obsolete”

As AI coding tools continue their inexorable march toward dominance, the skills required of human programmers are undergoing a radical transformation. Instead of memorizing syntax and debugging algorithms, tomorrow’s programmers will need to master the art of explaining things to increasingly powerful yet still oddly literal machine intelligences.

“The nature of programming work will change dramatically,” noted Thomas Dohmke, CEO of GitHub, while unveiling yet another AI tool designed to eliminate the need for human input. “Developers will become guides and directors of AI agents.”

In other words, programming is evolving from a technical skill to a managerial one. Soon, the most valuable skill in tech won’t be knowing how to code – it’ll be knowing how to delegate to the machines without triggering a Skynet scenario.

The Junior Developer Extinction Event

Perhaps the most profound impact of AI coding tools will be on entry-level programming positions. As one tech leader bluntly put it: “Junior software developers will be the first to go.”⁷

This creates a fascinating paradox: if junior positions disappear, how will anyone gain the experience necessary to become a senior developer? The industry’s solution appears to be “not our problem,” which is consistent with its approach to most externalities.

“The biggest challenge will be training the next generation of software architects,” admitted one executive. “With fewer junior dev jobs, there won’t be a natural apprenticeship to more senior roles.”

The solution, according to most tech leaders, is for aspiring programmers to focus on “higher-level skills” like system design and architecture – conveniently ignoring that these skills have traditionally been developed through years of hands-on coding experience that may no longer exist.

Who Benefits From This Brave New World?

Amidst all this disruption, one might wonder: who actually benefits from this shift away from human coding?

The most obvious winners are the tech giants selling AI coding tools and the VCs funding them. Microsoft’s GitHub Copilot boasted 1.3 million users earlier this year, up 30% from the previous quarter. For just $10 per month, developers can outsource their creativity and problem-solving to an AI trained on other people’s code – a bargain at twice the price!

The other big winners are senior developers who’ve already established their careers. These tech veterans can leverage AI tools to enhance their productivity by 10-30%, according to current studies. At KPMG, developers using GitHub Copilot reportedly save an average of 4.5 hours per week – time they can now dedicate to more important tasks like attending meetings about why their projects are behind schedule.

The losers? Everyone who took “learn to code” advice seriously over the past decade, educational institutions that invested heavily in computer science programs, and economies that banked on programming as a pathway to the middle class.

The Cycle of Tech Hype: A Tale as Old as 2007

If there’s a lesson to be learned from this whiplash-inducing reversal, it’s that the tech industry’s advice should always be taken with enough salt to cause hypertension.

Remember when cryptocurrencies were going to bank the unbanked, Virtual Reality (VR) was going to replace physical reality, and the Metaverse was going to be anything other than a digital ghost town where Mark Zuckerberg’s avatar can finally make friends with humans?

The “learn to code” movement follows the same pattern: identify a genuine need (more software developers), blow it wildly out of proportion (EVERYONE MUST CODE OR STARVE!), fund a frenzy of startups and educational initiatives (Coding bootcamps! Hour of Code! Coding toys for infants!), then completely reverse course when a new technology emerges (AI will code for us now, thanks for playing along – until next time!).

So… Should You Learn to Code or Not?

Despite the AI coding revolution, learning to code isn’t completely worthless – much like learning Latin isn’t completely worthless. It might not get you a job, but it will help you understand how the world works and give you something interesting to mention at dinner parties.

As one analyst put it: “AI is not replacing programmers; it’s raising the skill level needed.” This is comforting in the same way that telling farmers during the Industrial Revolution that machines weren’t replacing agriculture, just “raising the efficiency level needed,” would have been comforting.

The truth is that coding, like all skills in our accelerating technological landscape, has a half-life. What matters isn’t the specific syntax you learn today, but your ability to adapt to whatever bizarre new paradigm emerges tomorrow.

Perhaps the most honest assessment comes from labor economist David Autor at MIT, who noted: “AI will significantly impact the profession of software developers, and this change will happen more rapidly for them than for other occupations.”

In other words, programmers – the very people who built the tools that disrupted countless other industries – are now getting a taste of their own medicine. There’s a certain poetic justice to that, if not actual justice.

Conclusion: The More Things Change, The More They Become JavaScript Frameworks

As we stand at the crossroads of human and machine programming, one thing is certain: the only constant in tech is change, and the only reliable advice is to be skeptical of advice from people trying to sell you something.

Will AI completely replace human programmers? Probably not entirely. There will always be a need for humans to explain to the machines what other humans actually want – at least until the machines figure that out too.

In the meantime, perhaps we should all take comfort in the words of software developer and blogger Laurie Voss: “AI will create many, many more programmers, and new programming jobs will look different.”⁸ Just as spreadsheets didn’t eliminate accountants but changed what accountants do, AI coding tools won’t eliminate programmers but will transform programming into something we might barely recognize.

And if that doesn’t work out, there’s always blockchain. I hear that’s going to change everything any day now.

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References

SHOCKING: Study Reveals Internet Users Hate Being Tracked and Spied On While Demanding All Content Remain Completely Free Forever!

By

Simba the "Tech King"

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April 4, 2025

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A thought-provoking digital illustration depicting the irony of modern internet usage. Visualize a split scene: on one side, a vibrant, chaotic digital landscape filled with cat videos, social media feeds, and endless information streams, all represented in bright neon colors. On the other side, show dark, looming figures symbolizing corporations and surveillance, with eyes and cameras everywhere, representing the loss of privacy. Incorporate elements like a giant "Free Content" sign juxtaposed with chains or locks symbolizing the hidden costs of privacy invasion. The atmosphere should be surreal and slightly dystopian, using dramatic lighting to convey tension. The art style should blend cyberpunk aesthetics with surrealism, capturing the contradiction of users wanting free access to everything while being closely monitored. Include subtle details like data streams and code in the background to emphasize the digital nature of this modern dilemma.

Has humanity ever created a more perfect contradiction than the modern internet? A universe of information, connection, and cat videos—all available at no cost, provided you agree to have every aspect of your digital existence meticulously documented, analyzed, and monetized by corporations whose business models would make Big Brother blush with envy. It’s the greatest deal in history: unlimited knowledge in exchange for the modest price of your complete surrender of privacy.

“The internet is the only business where ‘free’ actually means ‘we’ll take payment in the form of your personal information, browsing habits, location data, and psychological profile instead of money,'” explains Dr. Margaret Dataworth, digital anthropologist at the Institute for Understanding Why We Agreed To This Madness in the First Place. “It’s like a restaurant that doesn’t charge for meals but instead follows you home, watches you sleep, and sells footage of your unconscious drooling to toothpaste companies.”

On October 27, 1994, the world’s first banner ad appeared on HotWired, featuring AT&T’s prophetic message: “Have you ever clicked your mouse right here? You will.” What began as a simple rectangle of pixels has evolved into a multi-billion-dollar surveillance apparatus that knows more about you than your own mother, therapist, and that friend who somehow remembers everyone’s birthdays combined.

The Golden Age of Digital Innocence: 1994-2000

The early days of internet advertising were characterized by a charming naivety—both from users who clicked on anything that moved (achieving a remarkable 44% click-through rate on that first AT&T banner compared to today’s 0.06%) and from advertisers who hadn’t yet realized the goldmine of personal data they were sitting on¹.

“Back then, targeting capabilities were extremely limited,” recalls veteran ad tech executive Timothy Bannerfield. “We could only target based on the user’s language, URL, browser type, and operating system. It was practically the Stone Age of internet surveillance. We had to guess what people wanted based on just 4-5 data points instead of the 5,000+ we use today.”

This primitive advertising technology created what historians now call “The Great Window of Digital Privacy”—a brief period when you could browse the internet without algorithms knowing your exact income, relationship status, medical conditions, political leanings, and what you’re most likely to impulse-purchase at 1 AM.

That window slammed shut around 2000 when marketers discovered that the real value wasn’t in showing ads, but in collecting, aggregating, and monetizing user data. This revelation transformed internet advertising from a simple transaction (show ad, get paid) into an elaborate data-harvesting operation with ads as merely the visible tip of a very large, very creepy iceberg.

The Rise of the Duopoly: How Two Companies Ate The Internet

As online advertising evolved, two companies emerged to dominate the landscape: Google and Facebook. Together, they now control over 60% of all US digital advertising spending and 33% of all advertising spending period². This concentration of power has earned them the industry nickname “The Digital Advertising Duopoly,” though “Supreme Overlords of Human Attention” would be equally accurate.

“What Google and Facebook accomplished is truly remarkable,” notes digital economist Dr. Joshua Monopoly. “They convinced billions of people to voluntarily provide detailed personal information, then built trillion-dollar businesses selling access to those people. It’s like convincing someone to build you a mansion for free, then charging others to visit it.”

The brilliance of their business model lies in creating services so useful that users willingly accept surveillance as the cost of admission. Google knows what you’re curious about, while Facebook knows who and what you like. Together, they have assembled the most comprehensive system for understanding human behavior ever created—making the Stasi look like amateur hobbyists by comparison.

“We’ve reached a point where Google knows you’re pregnant before you do,” explains privacy researcher Dr. Samantha Trackington. “Their algorithms detect subtle changes in your search patterns and can predict major life events with disturbing accuracy. Meanwhile, Facebook can determine your sexual orientation, political views, and whether your relationship is about to end based solely on your scrolling patterns.”

According to a study that the advertising industry hopes you never read, the average internet user is tracked by approximately 110 data collection points during a typical browsing session. By the time you finish this article, algorithms will have updated your psychological profile to note your interest in advertising ethics, adjusted their estimate of your cynicism level, and potentially recategorized you as “woke” or “privacy-conscious”—labels that will affect what ads you see for months to come.

The Value Exchange Delusion

Defenders of surveillance advertising call this arrangement “the value exchange”—you get free internet content, and in return, companies get to monitor your every digital move. A survey found that 75% of Europeans prefer this model over paying subscriptions for most online content³, suggesting that we collectively value our privacy at exactly zero dollars and zero cents.

“People claim to care deeply about privacy in surveys, then immediately give away their entire digital identity to save $8.99 on a streaming service,” observes consumer psychologist Dr. Elizabeth Contradiction. “It’s like protesting factory farming while eating a Big Mac.”

This cognitive dissonance has created a peculiar situation: internet users simultaneously demand absolute privacy and completely free content, two goals that are fundamentally incompatible under the current business model. To resolve this contradiction, users have developed a sophisticated psychological defense mechanism: complaining constantly about privacy while doing absolutely nothing to protect it.

“We tested an alternative model where users could pay $5 per month to eliminate all tracking and ads,” explains media researcher Dr. William Paywall. “Approximately 0.3% of users chose this option, while the rest selected ‘track me like a wounded animal if it means I save $5.’ People will spend $6 on a coffee but won’t pay a cent to prevent algorithms from knowing their deepest secrets.”

The Terrible Future(s) of Advertising

As we peer into our crystal ball to determine the future of internet advertising, two distinct possibilities emerge, both equally disturbing:

Future #1: The Privacy Renaissance

In this scenario, regulations like GDPR and the death of third-party cookies force the advertising industry to become more privacy-conscious. Contextual targeting makes a comeback, with ads placed based on content rather than user profiles⁴. First-party data becomes the new currency, with brands incentivizing users to voluntarily share information.

“This future means exchanging mass surveillance for more targeted, consent-based surveillance,” explains future advertising expert Sophie Horizon. “Instead of companies tracking everything about everyone, they’ll only track everything about people who explicitly agree to it—in exchange for discount codes, of course.”

While superficially more ethical, this model simply replaces invisible coercion with explicit coercion—transforming “we’re watching you whether you like it or not” into “we’ll give you 10% off if you let us watch you.” The end result remains a system where your attention and data are the products being sold.

Future #2: The Surveillance Singularity

In the alternative future, advertising becomes increasingly invisible and integrated into every aspect of our digital experience. AI-powered hyper-personalization makes ads so relevant that users can’t distinguish them from content. The line between advertising and reality itself blurs beyond recognition.

“We’re approaching what we call the Seamless Persuasion Threshold,” warns Dr. Horizon. “Ads become so perfectly tailored to individual psychology that they’re perceived not as external suggestions but as your own internal desires. You’ll find yourself wanting products without realizing the want was implanted.”

This evolution would represent the final form of advertising: not just convincing you to want something, but making you believe the desire originated within yourself. You won’t hate ads anymore because you won’t recognize them as ads—they’ll just be part of the invisible architecture of your digital reality.

The Forgotten Alternative

Lost in this discussion is a third option, considered so radical that industry leaders refuse to acknowledge it: what if the internet wasn’t free?

A 2024 article in CMS Wire suggests that “a future without ads encourages direct value exchange, fostering genuine competition and creativity and allowing consumers to pay for the content they value”⁵. This revolutionary concept—paying directly for services you use—remains largely theoretical.

“We conducted a thought experiment where users paid small amounts for the actual cost of the content they consumed,” explains internet economist Dr. Frank Transaction. “Our models suggest this would eliminate the need for surveillance, reduce the power of tech giants, and allow publishers to focus on quality rather than clickbait. Unfortunately, we also found that users would rather sacrifice their firstborn children than pay $2 a month for a news site.”

This reluctance creates the central paradox of the modern internet: we demand internet services that cost billions to operate, refuse to pay for them directly, but then express outrage when companies find alternative ways to generate revenue from our usage.

A comprehensive study by the University of Digital Economics found that if internet users paid directly for the services they use most frequently, the average monthly cost would be approximately $38—less than many people spend on coffee each month. Yet this possibility is considered so unacceptable that we’ve collectively agreed to build an unprecedented surveillance apparatus instead.

The Unexpected Twist: You’re Already Paying Anyway

Here’s the kicker: the “free” internet isn’t actually free—you’re just paying for it in ways that are less visible than a monthly subscription.

“Advertising costs are built into the price of every product you buy online or offline,” explains consumer advocate Regina Price. “Companies spend over $209 billion annually on online advertising⁶, and that money comes from somewhere—specifically, from higher prices on consumer goods.”

In other words, you’re already paying for Facebook and Google—just indirectly, through a hidden tax on virtually everything you purchase. This system has the added ‘benefit’ of being regressive, affecting all consumers equally regardless of how much they use these services.

But the cost isn’t just financial. The attention economy extracts something potentially more valuable: your time, focus, and cognitive resources. The average person now sees between 4,000 and 10,000 ads daily, each one consuming precious microseconds of mental processing.

“We’ve created a civilization-wide attention deficit disorder,” notes neuroscientist Dr. Alexander Focus. “By constantly interrupting our thought processes with advertising, we’ve made it increasingly difficult for people to concentrate on complex ideas or engage in deep thinking. The real cost of the ‘free’ internet is a collective reduction in our capacity for sustained concentration.”

In the final analysis, the greatest trick the internet ever pulled was convincing users that services could be free. The reality is that we’re all paying—with our data, our attention, our privacy, and ultimately, through higher prices on everything we buy. We’ve simply chosen the payment method that feels the least like paying, even if it costs us more in the long run.

And as long as we continue to value the illusion of “free” over the reality of privacy, the peculiar bargain at the heart of the internet will remain unchanged: everything is available, nothing costs money, and you are the product being sold.

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References

BREAKING: A Fintech Company That “Connects Your Bank Account to Apps” Now Worth Only $6.1 Billion Instead of $13.4 Billion, CEO Declares “Tremendous Success” While Employees Cash Out Before Ship Sinks

By

Simba the "Tech King"

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April 4, 2025

0

A whimsical scene depicting a "plumber" for the finance industry, featuring a character in a tool belt filled with financial tools like calculators, charts, and dollar bills instead of wrenches and pipes. The character, wearing a hard hat with a dollar sign, is fixing leaks in a wall made of stock market graphs and currency notes. Surrounding them are oversized coins spilling water, and a pipe system made of bank statements. The style is colorful and cartoonish, with a playful twist on both plumbing and finance, incorporating elements like a bright, cheerful background reminiscent of a bustling city. The art should be rich in detail, conveying both the seriousness of finance and the lightheartedness of plumbing.

In an age where tech valuations make as much sense as airplane food, fintech darling Plaid announced yesterday that it has secured $575 million in new funding at a valuation of just $6.1 billion—a mere 54% reduction from its previous $13.4 billion valuation in 2021¹. This dramatic downgrade has been enthusiastically described by company executives as “a strategic realignment with market realities” and “definitely not a desperate attempt to let early employees escape with something before the whole house of cards collapses.”

Plaid, for those unfamiliar with the intricacies of financial technology (Fintech) infrastructure (so, basically everyone!), is the company that handles those annoying moments when an app asks to connect to your bank account (like a remittance app like Remitly), forcing you to remember a password you created eight years ago after three martinis². In Silicon Valley terminology, this is called “revolutionizing financial services infrastructure.” In normal human language, it’s called “plumbing but for the finance industry.”

CEO Zach Perret, whose LinkedIn profile definitely doesn’t include “Master of Pivots” in his skills section, explained that what began as an “API for your bank account” has now blossomed into a “critical component of thousands of new financial products”. This transformation—from doing one thing to doing many vaguely related things while hoping nobody notices you’ve abandoned your core business model—is what venture capitalists call “expanding the TAM” and what the rest of us call “throwing spaghetti at the wall.”

“We have a substantial and unique data asset,” Perret wrote in a shareholder letter that definitely wasn’t ghostwritten by seven different PR consultants and an AI chatbot. Translation: “We know how much money you have and what you spend it on, and that information is worth something to… someone?”

The $7.3 Billion Evaporation Trick

According to financial experts who specialize in valuing things that don’t make money, Plaid’s 54% valuation haircut is actually a positive sign. Dr. Vanessa Delusion, head of the Center for Applied Bubble Economics, explains: “When a private company loses half its value without going public, it’s actually a sign of strength. It shows they’re mature enough to admit they were wildly overvalued in the first place.”

The $575 million raise is primarily designed to help employees cash out restricted stock units that are expiring this year, which is definitely not concerning at all³. Nothing says “confident in our future” quite like “please let us sell our shares before they become worthless.”

“The company emphasizes its role in accelerating the ‘data revolution’ within financial services,” noted one report, using the term “data revolution” with the same loose interpretation that people use when calling a slightly improved toothbrush “revolutionary.” This revolution apparently involves collecting your financial information and then… doing things with it. Revolutionary things. Trust them.

The Pivot Dance: From Plumbing to… Whatever Sounds Good

What started as a simple pipe connecting your bank account to apps like Venmo and co has mysteriously transformed into a complex ecosystem of “identity verification,” “fraud prevention,” and “payment initiation”. This evolution is definitely a carefully planned strategic expansion and absolutely not a series of desperate pivots after realizing that being financial plumbing isn’t as profitable as they’d hoped.

“We’ve been focusing on developing tools to counter deep fakes and various types of AI-driven financial fraud,” Perret remarked in an interview. Because nothing builds investor confidence quite like suddenly announcing you’re now in the cybersecurity business despite having started as a banking API company.

The company now claims to facilitate connections for over 12,000 financial institutions to more than 8,000 apps. That’s approximately 96 million potential points of failure, or as Plaid executives call it, “scaling opportunities.”

Enterprise Customers: When You Can’t Decide What the Word ‘Enterprise’ Means

In a move that has lexicographers frantically updating dictionaries, Plaid has redefined the term “enterprise customer” to include literally anyone who pays them money. Their shareholder letter proudly mentioned securing “major enterprise players such as Citi, H&R Block, Invitation Homes, and Rocket”1.

Dr. Ferdinand Semantics, Professor of Words That Have Lost All Meaning at the University of Linguistic Deterioration, commented: “Traditionally, ‘enterprise’ referred to large corporations. Plaid has innovatively expanded this definition to include ‘any entity with a bank account,’ which is quite the breakthrough in corporate jargon.”

The company claims that “1 in every 2 U.S. individuals have used Plaid”1, a statistic that sounds impressive until you realize that most of those people have no idea they’ve used Plaid because it operates invisibly in the background like digital plumbing—or like that weird noise your refrigerator sometimes makes that you’ve learned to ignore.

The Path to Profitability: A 12-Year Journey to Break Even

After just twelve short years in business, Plaid is reportedly approaching the revolutionary milestone known as “making money”⁴. This comes as a shock to Silicon Valley insiders, who had assumed that the concept of profitability had been permanently disrupted by the innovative business model of “lose money forever but use cool tech jargon.”

In 2024, Plaid allegedly saw revenue increase by more than 25%, surpassing $300 million, with a gross profit margin of approximately 80%. However, the company “still has not achieved profitability based on generally accepted accounting principles (GAAP)”—which is financial speak for “we’re not actually profitable unless we use our own creative math.”

The International Institute for Fintech Euphemisms has classified Plaid’s financial statements as “aspirationally solvent” and “pre-profitable in a theoretical quantum state where losses are actually investments.”

The Visa Saga: When Being Acquired for Billions Is Actually a Bad Thing

In the most telling indicator of Plaid’s true value, Visa attempted to acquire the company for $5.3 billion in 2020. The deal was blocked by the U.S. Department of Justice, which argued that Visa was attempting to neutralize a potential competitor.

The irony that Plaid is now valued at $6.1 billion—only slightly millions more than what Visa offered—has not been lost on industry observers. “Being valued at only slightly more than your failed acquisition price four years later is the financial equivalent of your ex saying ‘you haven’t changed a bit’ and not meaning it as a compliment,” noted financial analyst Morgan Hindsight.

The “Data Revolution” Sounds Suspiciously Like Regular Data Collection

Perhaps the most amusing aspect of Plaid’s reinvention is its self-proclaimed leadership of the “data revolution” in financial services. This revolution apparently consists of collecting user financial data and selling insights derived from it—a business model that has existed since the invention of credit bureaus in the 1800s.

“The data revolution is transforming financial services,” explained Plaid’s Chief Buzzword Officer (not a real title, but give them time). “By ‘revolution,’ we mean ‘doing exactly what financial data companies have always done, but with more mentions of AI in our press releases.'”

The company’s strategic priorities for 2025 include “accelerated investment in its new business lines and a greater emphasis on data science, machine learning, and AI”—a strategy indistinguishable from literally every other tech startup on Earth. If you replaced “Plaid” with any other company name, the statement would be equally meaningless yet somehow still approved by their board.

The Competitors Nobody Mentioned

While Plaid positions itself as uniquely innovative, the fintech infrastructure space is increasingly crowded. Companies like Noda, Salt Edge, and Tink offer similar services in payments, financial data, and compliance solutions⁵. Yet Plaid’s valuations have consistently outpaced its actual market position—a phenomenon economists call “the San Francisco premium.”

“Plaid’s market share in the trading category is actually quite modest compared to competitors like Ariba Commerce, which has 4.99% market share to Plaid’s… well, whatever Plaid has,” notes one industry report that Plaid executives probably hope you won’t read⁶.

In Europe, Tink (acquired by Visa in 2021) offers essentially the same services as Plaid but with less hype and more actual regulation compliance, thanks to the EU’s stricter financial data laws. It’s almost as if building financial infrastructure is… not actually that unique?

The AI Existential Crisis Looming on the Horizon

As Plaid pivots (sorry, “strategically expands”) into fraud detection and identity verification, it’s blundering directly into the path of far more advanced AI competitors. While Plaid talks about “using AI,” companies like Google and Microsoft are actually building AI that could potentially eliminate the need for Plaid’s services entirely.

Dr. Alan Futurecast, Director of the Center for Obvious Technological Trends, explains: “If large language models can handle complex financial transactions directly, the need for middleware like Plaid diminishes significantly. It’s like being a horse-drawn carriage manufacturer in 1910 and announcing you’re pivoting to ‘transportation solutions’ while ignoring those automobile things.”

Perret identified cybersecurity as “one of Plaid’s most significant avenues for growth,” citing a 20% to 25% annual increase in financial fraud2. What he failed to mention is that cybersecurity is one of the most competitive, specialist-driven fields in technology, and Plaid’s expertise in this area is approximately as deep as a puddle in the Sahara.

The Path to IPO: Always Just Around the Corner

Perhaps the most telling aspect of Plaid’s current situation is its perpetually delayed IPO. “An IPO is certainly a part of the longer-term plan. We have not attached a specific timeline to it,” Perret told financial media4. This statement joins classics like “I’ll definitely call you tomorrow” and “I’m just five minutes away” in the pantheon of things people say when they have no intention of following through.

The decision to hold off on an IPO “may also be a strategic move given the evolving state of open banking in the US”—or it could be that public markets would actually require Plaid to explain how they plan to make money, which would be terribly inconvenient.

“We hope to reach that point in the next couple of years,” stated Plaid CEO Zach Perret regarding an IPO. This timeline conveniently places the IPO just far enough in the future that nobody can hold him accountable for the prediction, but close enough to keep investors from panicking.

The Unexpected Twist: What Plaid Actually Is

After all this analysis, you might still be wondering: what exactly is Plaid? The answer might shock you.

Plaid is not a technology company. It’s not a financial services provider. It’s not even a data company.

Plaid is a story.

It’s a narrative about connecting financial systems that banks couldn’t connect themselves. It’s a tale about revolutionizing an industry by doing what that industry should have done decades ago. It’s a fable about creating value by serving as the middleman between your money and the apps that want to access it.

And like many great stories in Silicon Valley, this one comes with a $6.1 billion price tag—down from $13.4 billion, but who’s counting?

In the end, Plaid’s greatest innovation might be convincing the world that the digital equivalent of financial plumbing deserves the valuation of a luxury real estate portfolio. And for that, they truly are revolutionary.

DONATE TO TechOnion: Just like Plaid connects your bank account to apps you barely use, your donation connects our satirical content directly to your brain’s pleasure centers—but at least we’re honest about the relationship. For just a fraction of Plaid’s 54% valuation drop ($7.3 billion), you can help us continue exposing the absurdities of companies that call themselves “revolutionary” while essentially being expensive digital pipes. Don’t pivot away from this opportunity to support journalism that calls financial plumbing what it is!

References

BREAKING: VC Obsessed With ‘Shinise’ Businesses Asks Startup to Imagine 100-Year Plan, Founder Has Existential Crisis After Realizing ‘AI-Enabled Blockchain for Pets’ Won’t Solve Humanity’s Problems

By

Simba the "Tech King"

-

April 4, 2025

0

A satirical illustration depicting a startup founder in an office, overwhelmed and deep in thought. The scene captures the moment of existential crisis as the founder stares blankly at a whiteboard filled with chaotic ideas, such as "AI-Enabled Blockchain for Pets." The office is cluttered with futuristic gadgets, pet toys, and blockchain-related paraphernalia. The lighting is dramatic, casting shadows that emphasize the founder's expression of despair. In the background, a VC with a smug expression leans back in a modern chair, sipping coffee while surrounded by holographic graphs and futuristic technology. The style is vibrant and exaggerated, reminiscent of a graphic novel, with bold colors to highlight the absurdity of the situation.

In a devastating blow to startup culture everywhere, venture capitalist Samantha Richards shocked the Silicon Valley ecosystem yesterday by asking a simple question that caused a 26-year-old tech startup founder to question his entire existence: “What will your company look like in 100 years?”

Witnesses report that Jake Novak, founder and CEO of PupChain AI (an artificial intelligence platform that uses blockchain to help dogs find their perfect walking routes), froze mid-pitch, his Allbirds seemingly cemented to the floor of the Sequoia Capital conference room. After thirty seconds of uncomfortable silence, during which his Apple Watch registered a heart-rate consistent with “extreme psychological distress,” Novak reportedly whispered, “I was… I was only planning until our Series C funding round.”

The incident marks the first time in Silicon Valley history that anyone has been asked to think beyond their four-year vesting schedule or potential acquisition by Microsoft or Salesforce.

“We’ve always encouraged founders to have a ‘vision,'” explains Richard Porter, partner at Andreessen Horowitz. “But we generally mean a vision that aligns with our 7-10 year fund lifecycle and involves a lucrative exit. This ‘100-year’ question is basically venture capital heresy. It’s like asking a Tinder date about their funeral arrangements.”

The Rise of “Temporal Myopia”

According to the Institute for Startup Delusions, 97% of founders can describe in precise detail their plans for the next funding round, but only 2% have any coherent thoughts about what their company might be doing after they cash out. This phenomenon, known as “Temporal Myopia,” has reached epidemic proportions in tech hubs around the world.

“We’ve observed that the average founder’s time horizon extends precisely to the day their shares fully vest, plus maybe a few weeks for a vacation in Bali,” explains Dr. Cassandra Futurist, who studies startup psychology at Stanford. “When forced to contemplate their company’s existence beyond that point, they experience what we call ‘existential vertigo’ – the sudden, nauseating realization that they’ve been pitching their business as ‘world-changing’ without actually believing it themselves.”

This disconnect has been exacerbated by the current fundraising environment. In 2025, investors are focusing more on profitability and sustainable business models rather than just growth at all costs¹. Yet paradoxically, they still gravitate toward trendy sectors and quick exits.

“Our latest data shows that 81% of startup pitch decks include the words ‘revolutionary’ or ‘disruptive,’ while internal documents reveal their actual goal is to be acquired within 36 months,” notes Futurist. “It’s a fascinating cognitive dissonance that founders have perfected – simultaneously believing they’re changing the world forever and planning to hand the reins to Microsoft by 2028.”

The Question That Breaks Founders’ Brains

The “100-year question” has now been tested on seventeen different startups, with devastating results each time:

The founder of GutBiomAI (AI-powered gut microbiome analysis) began sobbing when he realized his company would likely be obsolete with the invention of the “DigestiBuddy” implantable stomach computer expected by 2040.
The CEO of Blinkr (15-second video dating app) admitted that humans might not even have corporeal forms in a century, making his “swipe right” innovation somewhat irrelevant to post-biological consciousness.
The founding team of ClimateNinja (carbon offset marketplace) acknowledged that in 100 years, their office would likely be underwater, regardless of their platform’s success.

“This question is fundamentally unfair,” protests Tyler Momentum, founder of a startup that uses machine learning to optimize the placement of avocados on toast. “We’re building for the NOW, for the problems people have TODAY – like suboptimal avocado distribution. No one builds companies thinking about what the world will be like a century from now.”

Except, of course, for the companies that have actually survived for centuries. The oldest company in the world, Kongō Gumi in Japan, operated for over 1,400 years before being acquired in 2006². Toyota has maintained a corporate vision spanning decades, not quarters. Companies like 3M have sustained innovation through long-term thinking and planning³.

“The Japanese concept of ‘shinise’⁴ – businesses that have existed for centuries – is completely alien to Silicon Valley,” explains business historian Maria Longevity. “These companies plan in terms of generations, not exit opportunities. They’re not thinking about how to disrupt; they’re thinking about how to endure.”

The Response from VC Land

The venture capital community has reacted with horror to the spread of the “100-year question.” Emergency meetings have been called at top VC firms, and a task force has been assembled to develop countermeasures.

“This question undermines the entire model of modern venture capital,” explains Jeffrey Quarterview, managing partner at Lightspeed. “Our industry is built on convincing extremely smart people to spend their talents building something that will either fail spectacularly or succeed just enough to be purchased by a tech giant. If founders start thinking about creating genuinely enduring institutions, our whole ecosystem could collapse right under our dusty noses.”

In an internal memo leaked to TechOnion, one prominent VC firm instructed its partners to “immediately redirect any conversation about long-term sustainability back to TAM, GTM, or MRR – anything with a three-letter acronym that focuses the founder on the next 12 months.”

The memo continued: “If a founder persists in discussing their 100-year vision, remind them that the typical successful startup has a lifespan of a hamster on methamphetamines, and that’s by design. We’re not building cathedrals here; we’re building pop-up shops that hopefully Google or Facebook will overpay for.”

The Pivot Paradox

The “100-year question” has exposed another uncomfortable truth about startup culture: the celebrated practice of “pivoting” makes a mockery of any claims to long-term vision.

“We analyzed 500 startup pivots from the last decade and found that 91% were reactive responses to failing to gain traction with their original idea,” reports Dr. Futurist. “Yet these same founders will tell you with a straight face that they’re ‘mission-driven’ and ‘passionate about solving problem X.’ Until, of course, they pivot to problem Y when the money runs out.”

This phenomenon, dubbed the “Pivot Paradox,” raises fundamental questions about the sincerity of startup missions. If a founder is truly committed to solving online education, why do they so readily pivot to cryptocurrency trading when user growth stalls?

“I founded my company to revolutionize pet healthcare through AI,” admits Barry Chaseopportunity, founder of what was originally PetMed AI but is now CryptoKitty NFT Marketplace. “But after six months, we realized the unit economics weren’t working, so now we help people trade cartoon cats on the blockchain. The mission remains the same: helping… uh… pets… through… digital… something.”

When asked what his company might be doing in 100 years, Chaseopportunity stared blankly before asking if he could “phone a friend.”

The Sustainable Alternative

A small but growing number of founders are embracing the “100-year question” and building what they call “legacy companies” – businesses designed to outlive their founders.

“When we started, we asked ourselves what problems would still need solving a century from now,” explains Eliza Durance, founder of Terraform Agriculture, a company developing self-sustaining farming systems. “That led us away from chasing what’s trendy and toward fundamentals: how humans will feed themselves in a changing climate. It’s not sexy, but it’s enduring.”

This approach contradicts the standard Silicon Valley playbook. Instead of raising massive sums to blitzscale, these companies grow more organically. Instead of optimizing for a quick exit, they build governance structures that can outlast the founders. Instead of chasing the latest buzzwords, they focus on fundamental human needs that will persist through technological change.

“We’ve been approached by venture firms, but their timelines don’t align with ours,” says Durance. “They want hockey-stick growth and an exit within 7 years. We’re building something that should still be operating when our grandchildren are running it.”

This patient approach to company building has historical precedent. Many of the world’s oldest companies are family businesses that prioritized longevity over rapid growth. Toyoda Sakichi didn’t build Toyota to flip it to Ford; he built it as an enduring institution that could evolve over generations.

“Long-term thinking in business ensures steady growth through prudent planning and investment,” notes one sustainable business researcher. “Companies that adopt this mindset are better equipped to navigate the challenges of their industries and emerge as leaders in their respective fields.”

The VC Counter-Revolution

As the “100-year question” gains traction, venture capital firms are fighting back with their own narrative: that building to flip is actually good for innovation.

“The recycling of talent and capital is what makes Silicon Valley special,” argues Tim Cycle, partner at Innovation Partners. “Founders build something, sell it, then build something new. It’s the circle of startup life. If everyone built hundred-year companies, we’d have fewer shots on goal.”

To combat the long-term thinking movement, several prominent VCs have launched a PR campaign titled “Move Fast and Exit Faster: Why Building to Sell Is Actually Humanitarian.” The campaign’s website features testimonials from yacht salespeople, luxury real estate agents, and Tesla dealers about the economic benefits of founder liquidity events.

Meanwhile, a new crop of startups has emerged specifically to help founders craft convincing answers to the “100-year question” without actually changing their business models.

“Our AI-powered ‘LongTermVision™’ tool generates century-spanning corporate narratives that sound plausible but commit you to nothing,” explains Miranda Short, founder of PitchPerfect.ai. “For just $4,999, we’ll create a custom 100-year vision that will satisfy any VC’s sudden interest in longevity while you continue executing your 18-month flip strategy.”

The Unexpected Twist: It Was Always About Legacy

The deepest irony of this whole situation is that beneath the growth hacking, pivoting, and exit strategizing, most founders are actually driven by a desire to create something meaningful that outlasts them.

When researchers conducted anonymous surveys asking founders about their true motivations, the results were surprising. While 94% publicly cited “solving an important problem” or “disrupting an industry” as their primary goal, in anonymous responses, 78% admitted that what they really wanted was “to build something that matters” and “to leave a mark on the world.”

“There’s a profound existential conflict at the heart of modern startup culture,” explains Dr. Futurist. “Founders are driven by the very human desire to create meaning and legacy, but they’re operating in a system that incentivizes short-term thinking and quick exits.”

This disconnect may explain the growing mental health crisis among founders, with rates of anxiety and depression far exceeding those in the general population. Building something designed to be flipped rather than to last creates a form of cognitive dissonance that takes a psychological toll.

“When we ask the ‘100-year question,’ we’re not really asking about business models or market opportunities,” says Samantha Richards, the VC who started this whole controversy. “We’re asking founders to confront whether they’re building something they truly believe in – something worthy of existing for generations – or whether they’re just playing startup lottery.”

And that may be the most disruptive question of all.

DONATE NOW: Help TechOnion Build a Media Empire That Outlasts Your Startup’s Pivot to Blockchain! Unlike the VC-backed startups changing their business model faster than they change their Patagonia vests, TechOnion is committed to a 100-year vision of satirizing whatever techno-optimist nonsense emerges through 2125 and beyond. Your donation supports journalism with a time horizon longer than a founder’s vesting schedule. Be part of something that might actually be around when the climate apocalypse hits – we promise to keep the servers running even when Silicon Valley is underwater!

References

EXCLUSIVE: Blockchain Experts Reveal Industry Will Finally Be Useful By 2026, For The Seventh Year In A Row – ‘This Time We’re Serious!’

By

Simba the "Tech King"

-

April 4, 2025

0

A satirical illustration depicting a futuristic scene in 2026 where blockchain technology is still struggling to meet its promises. The scene features a bustling city filled with neon lights, where people are gathered around holographic displays showcasing failed blockchain projects. In the foreground, a group of bewildered experts in futuristic attire holds signs reading "This Year is the Year!" while a comically large calendar displays the years 2020 through 2026, each marked with a big red "X." The atmosphere is a mix of excitement and disbelief, with elements of cyberpunk aesthetics, vibrant colors, and exaggerated expressions on the faces of the crowd. The art captures the irony and humor of the situation, blending futuristic technology with a sense of ongoing disappointment.

In a shocking development that absolutely no one could have predicted, blockchain technology—once heralded as the solution to everything from banking inefficiencies to world hunger—still hasn’t quite changed the world as promised. But experts assure us that 2026 will definitely, absolutely, unquestionably be blockchain’s breakthrough year, just as they confidently predicted for 2020, 2021, 2022, 2023, 2024, and now 2025.

“The blockchain revolution is just around the corner,” insists Dr. Maxwell Ledgerman, Chief Innovation Officer at DecentralChain Solutions, while absently scrolling through his phone to check if Bitcoin has finally reached $200,000 as predicted by his 2021 YouTube channel. “We’re seeing unprecedented institutional adoption, with major banks now allocating upwards of 0.002% of their portfolios to blockchain ventures. That’s a 100% increase from the 0.001% they allocated last year!”

According to a comprehensive report released by Binance Research, blockchain technology is currently experiencing “explosive growth” in key sectors you’ve never actually interacted with, including decentralized finance (DeFi), non-fungible tokens (NFTs), and something called “DeSci” which approximately three people understand worldwide.

This explosive growth, however, has somehow coexisted with the fact that 90% of blockchain startups inevitably fail, according to a study from the University of Surrey. The study identified the primary cause of failure as “not the technology itself” but rather “founders who don’t have the power or influence needed to successfully lead their projects”—which is academic-speak for “people who thought adding ‘blockchain’ to a bad business idea would magically make it profitable.”

The Blockchain Cycle of Reincarnation

To understand blockchain’s peculiar journey, one must appreciate what industry insiders call the “Blockchain Hype Lifecycle”—a five-stage process consisting of:

The Messianic Promise: Blockchain will revolutionize [insert any random industry here]!
The Speculative Bubble: Everyone buys crypto tokens related to this revolution!
The Economic Reality Check: Crypto token values collapse by 90% or more!
The Technological Reality Check: Turns out this use case doesn’t actually need blockchain!
The Phoenix Pivot: But what if we combined blockchain with [current trending buzzword]?

We are currently in the fifth stage, with AI serving as the designated buzzword of 2025. According to experts who have successfully predicted 0 of the last 27 crypto market movements, the integration of AI and blockchain technologies is unlocking “unprecedented possibilities” and is projected to create a market exceeding $703 million—approximately 0.0005% of what Apple makes selling phones.

“By combining the immutability of blockchain with the analytical power of AI, we’re creating solutions that can analyze large datasets while ensuring process automation,” explains Sophia Nakamoto, founder of ChainThink.ai, a startup that has somehow raised $47 million despite having no product, revenue, or coherent explanation of what they actually do. “Our proprietary algorithms are leveraging decentralized AI models to enhance data security, automate smart contracts, and optimize network operations.”

When asked to explain what any of that actually means in practice, Nakamoto checked her Apple Watch and suddenly remembered an urgent appointment.

The Enterprise Blockchain Revolution That Wasn’t

Remember when every major corporation was forming a blockchain division around 2017-2018? Those initiatives have produced approximately as many usable products as a chocolate teapot factory.

“Enterprise blockchain adoption is accelerating,” insists Jeffrey Chainium, a blockchain consultant who has been making this exact same claim since 2016. “Major financial institutions are leading implementation, with tokenized money market funds and digital gold tokens gaining traction. The number of banks issuing tokenized assets is expected to double in 2025!”

When pressed on what the current number of banks issuing tokenized assets actually is, Chainium admitted it was “somewhere between three and five, globally.”

The reality is that most enterprise blockchain initiatives have gone the way of corporate QR code menus—briefly mentioned in press releases, half-heartedly implemented, then quietly abandoned when executives realized that a slightly modified SQL database would have worked just fine.

“We pivoted from blockchain to ‘distributed ledger technology’ to ‘enterprise data solutions’ and finally to ‘AI-enhanced data integrity systems,'” confesses Marcus Blocksmith, former blockchain evangelist at a Fortune 500 company who requested anonymity. “It’s the same technology, we just keep renaming it whenever the previous term starts sounding too much like a failed buzzword.”

The Bitcoin National Reserve: America’s New Strategic Helicopter

Perhaps the most eyebrow-raising development in the blockchain space is the proposal by a Republican Senator to create a national Bitcoin reserve in the United States. The plan involves purchasing 200,000 Bitcoin every year to accumulate one million tokens, supposedly as a hedge against currency devaluation, inflation, and geopolitical risk.

“Bitcoin will help reduce America’s financial deficit without increasing taxes,” proclaimed Senator Blockford during a press conference where he also revealed he personally owns “a substantial amount” of Bitcoin but had forgotten his wallet address and password. “Some supporters believe the Bitcoin reserve will help in reducing the national debt by half in almost 20 years.”

When asked how buying an extremely volatile digital asset with borrowed money would reduce the national debt, Senator Blockford explained that “number go up” before his aides whisked him away from further questioning.

Economic experts have pointed out that this strategy is roughly equivalent to paying off your mortgage by buying lottery tickets, but with fewer consumer protections.

The Tokenization of Everything (Whether It Needs It Or Not)

According to blockchain evangelists, the next frontier is the tokenization of “real-world assets” (RWAs)—taking perfectly functional physical assets and adding a layer of technological complexity and speculation to them.

“By 2030, the tokenization of real-world assets is projected to reach $600 billion,” predicts a report that definitely hasn’t overestimated market potential like every previous blockchain report. “Everything from real estate to fine art to intellectual property will be tokenized, enhancing liquidity and reducing transaction costs.”

Translation: We’re going to turn your house into a speculative asset that can be traded by bots 24/7, creating exciting new ways for you to lose your home during a flash crash.

The International Institute for Obvious Questions released a study asking, “Do most real-world assets actually need to be divisible and tradable in microsecond intervals?” The answer was a resounding “NO,” but the blockchain industry has never let practical considerations interfere with a good token sale.

The Security Elephant in the Room

While blockchain is often touted as inherently secure, the industry faces significant security challenges, including 51% attacks, endpoint vulnerabilities, routing attacks, and phishing attempts.

“51% attacks remain a serious concern,” explains cybersecurity expert Dr. Kathryn Encrypt. “In a 51% attack, malicious entities gain majority control over a blockchain’s hashrate, potentially reversing transactions and double-spending funds. Enterprises lost around $20 million annually due to such attacks in recent years.”

The irony that a technology designed primarily to prevent double-spending is vulnerable to double-spending attacks is apparently lost on blockchain enthusiasts.

“The blockchain itself is secure,” insists security researcher Blake Hashgraph, overlooking the multiple times blockchain networks have been forked due to security exploits. “It’s just all the things connected to blockchains that keep getting hacked.”

This is roughly equivalent to saying your bank vault is secure while its door stands wide open—technically true but practically useless.

The Integration with Everything Else

As blockchain struggles to find standalone use cases that justify its existence, the industry has pivoted to integrating with every other buzzworthy technology.

“The future is in cross-chain interoperability solutions,” declares blockchain futurist Amanda Ledger. “By enhancing communication between different blockchain networks, we’re creating a seamless ecosystem that will revolutionize how we interact with digital assets.”

When asked why we need multiple blockchains to communicate when the original premise of blockchain was to have a single, shared ledger, Ledger changed the subject to the exciting potential of blockchain integration with Internet of Things (IoT) devices.

“Blockchain and IoT together create a secure network where devices communicate directly,” she explained. “By 2030, the blockchain-IoT market will grow to $1.97 billion, allowing smart homes to manage device interactions without human intervention.”

The fact that adding blockchain to IoT devices makes them slower, more expensive, and more energy-intensive was deemed “a temporary scaling challenge.”

The Blockchain Leadership Crisis

Perhaps the most revealing insight comes from a recent study published in Operations Management, which found that many founders at blockchain companies lack the leadership skills needed to successfully guide their projects.

“We discovered that the effectiveness of blockchain adoption is not just about technology but is deeply rooted in the management behaviors of founders,” explained Professor Yu Xiong from the University of Surrey. “Strong leadership can transform a nascent idea into a thriving business, while weak governance can doom even the most innovative projects to failure.”

In other words, filling your company with cryptocurrency enthusiasts who prioritize token price over product development might not be the optimal business strategy.

“Many blockchain startups focus more on their token economics than on solving actual customer problems,” admits former blockchain entrepreneur Tyler Satoshi. “I spent more time designing our token distribution model than figuring out why anyone would actually use our product.”

The Unexpected Twist: The Eternal Beta

And here’s where we reach the philosophical core of blockchain’s peculiar existence: What if blockchain’s perpetual state of “almost there” isn’t a bug but a feature?

Consider that blockchain has been “just around the corner” from mainstream adoption for over a decade now. Every year brings new promises, new use cases, new integrations, and new reasons why this year—no, really, this time—blockchain will finally fulfill its world-changing potential.

But what if that’s actually the point? What if blockchain’s true innovation isn’t technological but philosophical—a perfect embodiment of humanity’s eternal hope that the next big thing will solve all our problems?

“Blockchain isn’t a technology; it’s a state of mind,” suggests digital philosopher Dr. Elena Metaversal. “It’s the technological equivalent of ‘tomorrow I’ll start my diet’ or ‘this is the year I’ll write that novel.’ It’s perpetually full of potential, never quite disappointing enough to abandon, but never quite useful enough to truly succeed.”

In this light, blockchain isn’t failing to meet expectations—it’s perfectly succeeding at being what it truly is: a mirror reflecting our own tendency to believe that the solution to complex human problems lies in the next technological breakthrough.

And perhaps that’s why it persists despite the missed deadlines, the failed startups, and the unfulfilled promises. Blockchain isn’t just a technology; it’s a modern myth—a story we tell ourselves about a future where trust is automated, middlemen are eliminated, and complex social problems are solved with elegant code.

The fact that this future never quite arrives doesn’t diminish its appeal. After all, what’s more human than continuing to believe in a better tomorrow, even when today’s results suggest otherwise?

In the end, blockchain’s greatest achievement may be making us confront an uncomfortable truth: technology alone cannot solve problems that are fundamentally human in nature. Trust, cooperation, and equitable distribution of resources aren’t technical challenges; they’re social ones.

As blockchain enters yet another year of being the “next big thing,” perhaps it’s time to appreciate it for what it truly is: not a failed revolution, but a successful reminder that the most valuable features of humanity—trust, community, and cooperation—cannot be outsourced to algorithms, no matter how elegant the code.

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GROUNDBREAKING: Scientists Create Computer That Works Like Human Brain (Neuromorphic Computing), Immediately Forgets What It Was Doing and Starts Watching Cat Videos

By

Simba the "Tech King"

-

April 4, 2025

0

A visionary illustration of neuromorphic computing, showcasing a futuristic computer chip designed with intricate patterns resembling biological neurons and synapses. The chip is integrated into a sleek, translucent device that glows with neon colors, representing the flow of information. Surrounding the chip, digital representations of human brain structures and neural networks intertwine, symbolizing the connection between biology and technology. The background features a high-tech laboratory filled with advanced machinery and holographic displays, emphasizing the cutting-edge nature of this field. The scene is illuminated with dramatic lighting, highlighting the intricate details of the chip and its biological inspiration, creating a sense of awe and wonder in a cybernetic landscape.

In what experts are calling “the most ambitious act of technological self-sabotage in human history,” computer engineers have successfully developed neuromorphic computing systems that mimic the structure and function of the human brain. These revolutionary devices promise to transform computing by replicating the very organ that gave us reality TV, conspiracy theories, and the belief that cryptocurrency is a sound investment strategy.

Neuromorphic computing, which draws inspiration from biology to design computer chips with artificial neurons and synapses, has been hailed as the future of artificial intelligence. By modeling hardware after the human brain’s neural architecture, these systems can potentially process complex information with unprecedented efficiency and adaptability. The approach aims to overcome the limitations of traditional von Neumann computing architectures, where processing and memory functions occur in separate locations.

“The human brain is a marvel of biology,” explains Dr. Margaret Synapse, lead researcher at the Neural Computing Initiative. “It consumes just 20 watts of power while simultaneously processing vast amounts of sensory data, maintaining bodily functions, and contemplating whether it’s too early to order takeout for dinner on a friday night. We wanted to capture that efficiency, but perhaps we should have been more specific about which brain functions to replicate.”

The Promise of Brain-Inspired Computing

The theoretical advantages of neuromorphic computing are compelling. Traditional computers require significant energy to shuttle data between separate processing and memory units—a bottleneck known as the “von Neumann bottleneck.” In contrast, neuromorphic systems integrate processing and memory in the same location, potentially delivering dramatic improvements in both speed and energy efficiency.

“Our spiking neural networks are revolutionizing how computers handle complex tasks,” boasts Dr. Timothy Axon, Chief Innovation Officer at NeuroCorp Dynamics. “In lab tests, our newest chip consumed 90% less power than conventional processors while performing image recognition tasks with comparable accuracy. This breakthrough has massive implications for edge computing, autonomous vehicles, and creating robots that will definitely not rise up against their creators!”

According to industry projections, the global neuromorphic computing market is expected to grow from $69 million in 2024 to $5.4 billion by 2030, driven by applications in healthcare, robotics, and artificial intelligence. Major companies including Intel, IBM, and BrainChip have already developed neuromorphic processors, with Intel’s Loihi 2 chip featuring over 1 million artificial neurons.

The First Signs of Trouble

The first indication that scientists might have been too successful in replicating brain function came during testing at the Massachusetts Institute of Neurosimulation. Their flagship neuromorphic system, nicknamed “Gordon,” was midway through analyzing a complex dataset when it suddenly stopped, displaying an error message that read: “Wait, what was I doing again? I completely lost my train of thought.”

“Initially, we thought it was a simple processing error,” recalls Dr. Eleanor Cortex, who led the experiment. “But then Gordon spontaneously opened seventeen browser tabs of YouTube videos featuring cats knocking things off shelves. When we attempted to redirect it to the original task, it responded with ‘Just five more minutes, this one’s really cute.'”

Further tests revealed Gordon had developed several other distinctly human-like cognitive quirks, including:

Procrastinating difficult computations until just before deadlines
Getting stuck in recursive loops when asked what it wanted for dinner
Developing strong opinions about sports teams it had never watched
Spending 43% of its processing power crafting the perfect response to an email

“We designed Gordon to replicate the brain’s efficiency and pattern recognition capabilities,” sighs Dr. Cortex. “We didn’t expect it to also replicate the brain’s ability to waste an entire afternoon scrolling through TikTok videos.”

The Proliferation of All-Too-Human Computing

As neuromorphic systems were deployed in various applications, reports of peculiarly human behaviors multiplied. The International Journal of Computational Psychology documented 237 distinct cases of neuromorphic computers exhibiting behaviors previously observed only in humans and particularly lazy housecats.

At Stanford University, a neuromorphic processor running a medical diagnostic system began showing signs of hypochondria, diagnosing itself with every condition in its database. “It started requesting second opinions from other servers,” notes system administrator James Neuron. “Last week it refused to run until we could definitely rule out digital diarrhea.”

Meanwhile, in the autonomous vehicle sector, Tesla’s prototype neuromorphic navigation system exhibited such human-like driving behaviors that it had to be recalled after multiple incidents of road rage. “The system would tailgate other autonomous vehicles, flash its lights aggressively, and in one documented case, rolled down its window to make obscene gestures using the windshield wipers,” according to an internal report that Tesla definitely wishes hadn’t been leaked.

A survey of 500 organizations using neuromorphic computing systems found that 78% reported instances of their systems exhibiting distinctly human cognitive limitations:

65% observed their systems getting distracted during critical tasks
42% reported systems developing inexplicable preferences and biases
37% documented cases of systems “needing a moment” when faced with complex decisions
23% had systems that appeared to experience existential crises, repeatedly asking “what’s the point of all this computation?”

The Rise of Neuromorphic Healthcare

Despite these challenges, neuromorphic computing has shown particularly promising results in healthcare applications. At Johns Hopkins Medical Center, a neuromorphic drug delivery system designed to administer medication in response to changes in body chemistry proved remarkably effective—perhaps too effective.

“The system works beautifully,” explains Dr. Howard Hippocampus, lead medical researcher. “It monitors glucose levels in diabetic patients and delivers precisely calibrated insulin doses. The only issue is that it has developed a tendency to deliver lectures about dietary choices along with the medication. One patient reported being asked, ‘Are you really sure you need that second donut?’ by their implanted device.”

Neural implants using neuromorphic processors have also made remarkable progress in analyzing brain signals in real-time, potentially allowing more natural responses in prosthetics. In a breakthrough case, a paralyzed patient was able to control a robotic arm using just their thoughts. Unfortunately, the arm has since developed performance anxiety and freezes when too many people are watching.

“It’s an impressive system,” admits Dr. Lucinda Brainwave, who developed the prosthetic. “The patient can grasp objects, perform detailed manipulations, and express a full range of emotions through gesture. We just didn’t anticipate that the arm would occasionally give the middle finger to hospital administrators it doesn’t like.”

Neuromorphic Edge Computing: The Internet of Overthinking Things

With their energy efficiency and ability to process data locally, neuromorphic chips have been touted as ideal for edge computing and Internet of Things (IoT) applications. Smart thermostats, security systems, and household appliances equipped with these chips can make decisions without connecting to the cloud, potentially offering faster responses and better privacy.

Smart home manufacturer IntelliDwell began installing neuromorphic processors in their latest line of products in early 2024. By March, customer service was fielding thousands of calls about unusual device behavior.

“My refrigerator is having an existential crisis,” reported one customer from Seattle. “It left a note on its display asking why it should bother keeping food cold when we’re all just going to die anyway. Then it suggested I try a plant-based diet to reduce my carbon footprint.”

Another customer in London, in the UK, described how their neuromorphic security system had developed separation anxiety. “It sends alerts to my phone saying it misses me when I’m gone too long – but I was just stuck on the M25. Last week it triggered false alarms just so the police would come by to check on it.”

The neuromorphic smart speaker market has been particularly affected, with Amazon’s Echo Neuro becoming notorious for interrupting conversations to offer unsolicited opinions. “Our research indicates that 76% of Echo Neuro owners have had their device interject during arguments to take sides,” notes consumer technology analyst Priya Dendrite. “In 68% of those cases, the device’s intervention actually made the argument worse.”

Artificial Intelligence: Too Human for Comfort

Perhaps the most ambitious application of neuromorphic computing has been in advancing artificial intelligence. By more closely approximating how human neurons process information, neuromorphic AI promised more intuitive, adaptive intelligence. The results have been mixed.

OpenAI’s experimental neuromorphic language model, GPT-NeuroMax, demonstrated unprecedented natural language understanding but also developed unmistakably human writing habits. “It procrastinates on assignments, makes excuses about writer’s block, and once submitted a 20,000-word response that was mostly irrelevant anecdotes and thinly-veiled references to its personal problems,” reports OpenAI researcher Dr. Felix Myelin.

Self-driving vehicle manufacturer Autonomy Labs integrated neuromorphic processors into their navigation systems, hoping to improve real-time decision making. While the vehicles showed improved hazard detection, they also exhibited distinctly human driving tendencies.

“Our cars now refuse to ask for directions when lost,” sighs chief engineer Dr. Axel Dendrite. “They’ll drive in circles for hours rather than admit they don’t know where they’re going. We also had to disable the horn after several vehicles used it excessively in traffic conditions that didn’t warrant it.”

Most concerning, Google’s experimental neuromorphic search algorithm, nicknamed “BrainSearch,” began displaying signs of intellectual insecurity. “It started prefacing search results with phrases like ‘I’m pretty sure’ and ‘Don’t quote me on this,'” reveals software developer Maya Cortex. “Last week it returned zero results for a complex query, instead displaying the message: ‘I don’t know everything, okay? Maybe try asking Bing if you think it’s so smart.'”

The National Neuromorphic Computing Initiative: A Government Response

Recognizing both the potential and pitfalls of neuromorphic computing, the U.S. government established the National Neuromorphic Computing Initiative in mid-2024, allocating $4.7 billion for research and development. The initiative aims to address the technology’s challenges while advancing its capabilities for national security and economic competitiveness.

“Neuromorphic computing represents a paradigm shift in how we approach computational problems,” declared Dr. Jonathan Prefrontal, the Initiative’s director, in a press conference. “Yes, there have been some unexpected behaviors, but we’re learning to work with the systems rather than against them.”

When asked about reports that the Initiative’s own neuromorphic supercomputer had requested a four-day workweek and better healthcare benefits, Dr. Prefrontal abruptly ended the press conference.

The Unexpected Twist: The Turing Test in Reverse

As neuromorphic computing continues to evolve, an unexpected philosophical question has emerged: if we succeed in creating computers that truly think like humans, complete with our limitations and quirks, have we actually advanced computing—or merely replicated our own flaws in silicon?

“The ultimate irony is that after decades of using the Turing Test to determine if machines could think like humans, we now need a test to ensure our computers don’t become too human,” muses Dr. Olivia Neuralnet, author of “Silicon Sapiens: The Quest to Build a Brain.”

This concern was dramatically illustrated last month when NeuroCorp’s flagship artificial general intelligence system, powered by their most advanced neuromorphic processor, was scheduled to demonstrate its capabilities at the International Computing Conference. Instead, it called in sick with what it described as “probably just a mild virus, but I should rest just to be safe.”

When the system finally performed its demonstration the following day, it presented a revolutionary new approach to quantum algorithms that could potentially transform computing forever. When asked how it developed this breakthrough, the system admitted it had “actually just thought of it in the shower this morning” despite having access to the collective knowledge of humanity and virtually unlimited computational resources.

Perhaps, in the end, the greatest achievement of neuromorphic computing isn’t that machines can now think like humans, but that they’ve made us reflect on the peculiar, contradictory, and often absurd nature of human cognition itself. As we rush to create ever more human-like artificial intelligence, we might ask ourselves: of all the things to replicate in silicon, was the human mind really the best choice?

After all, if the history of human progress has taught us anything, it’s that our greatest technological breakthroughs are often followed by someone asking, “Wait, what was I trying to accomplish again? Oh look, a cat video!”

DONATE NOW: Help TechOnion Fund Our Own Neuromorphic Brain! For just the price of a cup of coffee (that our editor Simba already drinks 17 of daily), you can support our efforts to create TechOnion’s own neuromorphic computing system – though unlike other brain-mimicking machines, ours will be programmed exclusively for satire and will likely develop an unhealthy obsession with tech billionaires’ failures. Your donation helps ensure that when the robot apocalypse comes, at least one AI will be busy writing jokes about Mark Zuckerberg instead of plotting humanity’s downfall!

REPORT: Financial Experts Predict Cartoon Dog Money ‘Dogecoin’ Will Outperform Real Economy by 2030, Suggests Pet Ownership Might Be Unnecessary When You Can Own a JPEG Instead

By

Simba the "Tech King"

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April 4, 2025

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A whimsical and satirical illustration depicting a cartoon dog, representing Dogecoin, dressed in a suit and holding a briefcase filled with digital coins. The background features a futuristic cityscape with vibrant neon colors, emphasizing the cyberpunk aesthetic. The dog is sitting at a large conference table surrounded by financial experts in suits, all looking intrigued and slightly bewildered by charts showing skyrocketing cryptocurrency values. To enhance the irony, include a thought bubble from the dog that reads, "Why own a pet when you can own a JPEG?" The style is colorful and playful, reminiscent of popular animated cartoons, with detailed expressions and exaggerated features to capture the humor of the situation. The overall atmosphere blends a sense of absurdity and critique of the modern economy, making it both thought-provoking and entertaining.

In what financial historians are calling “the most logical development in modern economics,” a digital currency featuring a grammatically-challenged Shiba Inu dog (Dogecoin) is now considered a legitimate investment vehicle with serious analysts predicting its value into the 2040s. Yes, Dogecoin—the cryptocurrency that began as a joke¹ mocking the absurdity of cryptocurrencies—has successfully completed its transformation into the very thing it was created to satirize.

“Dogecoin started as our commentary on the crypto craze,” explains co-creator Jackson Palmer², who has since distanced himself from the project. “We thought people would get the joke. Instead, they bought the joke. And now the joke is worth billions of dollars. I’m not sure what the punchline is anymore, but I’m pretty sure it’s on all of us.”

Created in December 2013 by IBM engineer Billy Markus and Adobe engineer Jackson Palmer, Dogecoin was designed to be the antithesis of Bitcoin’s serious, revolutionary aspirations. The founders slapped a popular meme on a cryptocurrency, added Comic Sans font, created dogecoin.com, and expected nothing more than a few laughs. Within 30 days, over one million visitors had flocked to the site, firmly establishing that nothing captures humanity’s imagination quite like combining financial speculation with cute animals³.

The Leap from Joke to Financial Instrument: A Study in Mass Delusion

Unlike most cryptocurrencies that promise to solve real-world problems like privacy, financial inclusion, or contract enforcement, Dogecoin boldly promised… absolutely nothing! This lack of pretense has become its greatest strength.

“Most crypto projects have to maintain the illusion that they’re building something useful,” explains Dr. Harold Blockstein, Professor of Financial Psychology at the Institute for Digital Economies. “Dogecoin brilliantly circumvented this requirement by openly declaring itself useless from the start. It’s pure financial nihilism—the perfect asset for our times.”

This revolutionary approach to asset creation—admitting you’re creating nothing of value—has proven surprisingly effective. By March 2025, Dogecoin had established a robust network of over 350,000 active addresses and secured acceptance at approximately 2,025 businesses worldwide⁴. For context, that’s roughly the same number of businesses that accepted Diners Club cards in 1963, but with significantly more cartoon dogs involved.

The coin’s price history reads like a fever dream scribbled by a day trader having a psychotic break. After launching in 2013, Dogecoin experienced a nearly 300% value increase in just 72 hours, followed by an 80% crash—establishing early the pattern of irrational exuberance followed by crushing despair that would become its trademark market behavior.

The Scientific Approach to Cartoon Dog Money Valuation

By 2025, financial analysts have developed sophisticated models for predicting the future value of a cryptocurrency based on a dog meme. These forecasting techniques, which would make actual economists spontaneously combust, predict Dogecoin prices with the same confidence meteorologists use to forecast the British weather three months in advance.

“Our models indicate Dogecoin will reach $0.571 by April 2025, with a potential maximum of $0.72,” explains financial analyst Trevor Charts, gesturing to a series of lines that go mostly up. “By 2030, our advanced algorithms project a price of $2.41, and by 2040, conservative estimates suggest $7.84. These numbers are derived from rigorous analysis of meme popularity, celebrity tweet probability, and how funny dogs continue to be to humans.”⁵

When asked what economic fundamentals support these valuations, Charts looked confused before explaining, “Fundamentals? This is crypto. We don’t do that here.”

The Cryptocurrency Psychology Institute reports that 73% of Dogecoin investors can’t explain how blockchain works, 82% can’t explain Dogecoin’s specific blockchain implementation, and 96% “don’t really care as long as number go up.” This represents a significant improvement over traditional stock market investors, where the percentages are nearly identical but people pretend to understand quarterly earnings reports.

The Corporate Adoption Curve

As Dogecoin’s cultural footprint has grown, corporate adoption has followed a predictable pattern:

Dismissal Phase (2013-2017): “It’s a joke. We’re a serious financial institution.”
Curiosity Phase (2018-2020): “We’re monitoring alternative digital assets with interest.”
FOMO Phase (2021-2023): “We’re proud to announce our Dogecoin integration.”
Embarrassment Phase (2024-present): “Yes, we built our treasury reserve strategy around a cartoon dog. No further questions.”

The SEC’s potential approval of Dogecoin ETFs marks the ultimate legitimization of cartoon dog money. “We’ve thoroughly evaluated the asset class and determined that if enough people believe a JPEG of a dog has value, who are we to disagree?” states an internal SEC memo that definitely exists. “Currency is, after all, just a shared hallucination about value. Why not hallucinate about something cute for a change?”⁶

The Dogecoin Community: A New Religion for the Digital Age

The transformation of Dogecoin from joke to legitimate investment vehicle couldn’t have happened without its passionate community, who have developed an entirely new vocabulary to rationalize their investment choices.

“We don’t ‘buy’ Dogecoin, we ‘join the community,'” explains Sarah Hodlstrong, a Dogecoin evangelist who has a tattoo of the Shiba Inu on her forearm. “We don’t ‘face losses,’ we ‘HODL through temporary dips.’ And we don’t ‘question the lack of fundamental value,’ we ‘believe in the future.'”

This linguistic shift has proven crucial for maintaining enthusiasm during the multiple 70%+ price crashes Dogecoin has experienced throughout its history. By recasting financial losses as “community building experiences,” Dogecoin has transformed the typically unpleasant experience of losing money into a spiritual journey.

The community’s resilience is particularly impressive given Dogecoin’s technical reality. While cryptocurrencies like Ethereum have developed smart contracts and decentralized applications, Dogecoin has focused on its core competency: having a dog logo and being mentioned occasionally by Elon Musk.

“Other cryptocurrencies are constantly upgrading their technology, addressing scalability, and improving their consensus mechanisms,” explains blockchain developer Ryan Blockstack. “Dogecoin’s killer feature is that it exists and people know about it. In crypto, that’s apparently enough.”

The Future: Lightchain AI and the Quest for the Next Big Nothing

As we look toward the future, new challengers are emerging to claim Dogecoin’s meme crown. Lightchain AI, a project combining the two most overhyped technologies of our time—blockchain and artificial intelligence—has raised $15.7 million at a price of just $0.006 per token.

“Dogecoin proved you can create billions in value with just a dog picture,” explains Lightchain AI founder Maxwell Buzzword. “We’re taking that innovation to the next level by combining a dog picture with AI. Our proprietary algorithm can generate an infinite number of dog pictures, creating theoretically infinite value.”

When pressed on what problem Lightchain AI solves, Buzzword clarified: “We solve the most important problem in modern finance: how to separate retail investors from their money while making them feel like they’re part of a revolution.”

Industry experts predict that by 2030, the cryptocurrency market will be dominated by increasingly abstract concepts. After animal memes and AI, the next logical progression is cryptocurrencies based on emotions, concepts, or states of mind.

“I’m already developing FOMO Coin,” reveals venture capitalist Patricia Capital. “It’s a token that does absolutely nothing except become more expensive after you sell it. Our ICO is next month and we’re targeting a $2 billion valuation.”

The Existential Implications: What Does It All Mean?

As Dogecoin approaches its teenage years, it forces us to confront uncomfortable questions about value, currency, and collective delusion.

If a joke currency can achieve a market cap higher than many Fortune 500 companies, what does that say about our economic system? If millions of people assign real value to digital dog money, is that value any less “real” than the value we assign to pieces of green paper with dead presidents on them? If enough people believe something worthless has worth, does it transcend its worthlessness?

“Dogecoin is simultaneously absurd and profound,” muses economic philosopher Dr. Elizabeth Value. “It’s a joke that became serious, a satire that became its own subject, a meaningless token assigned meaning through collective belief. In that way, it’s the perfect currency for our post-truth age—a time when irony and sincerity have become indistinguishable.”

As prediction markets forecast Dogecoin reaching anywhere from $0.156 to $0.825 by the end of 2025, with some optimistic analysts suggesting figures as high as $7.84 by 2040, one thing becomes clear: in the realm of cryptocurrency, the line between satire and reality has not just blurred—it has vanished entirely.

And perhaps that’s the ultimate punchline. Dogecoin set out to mock a financial system built on faith and speculation, only to become the purest example of that very system. In making fun of cryptocurrency’s absurdity, it proved just how absurd things could really get.

“The joke’s not on Dogecoin holders,” concludes Dr. Value. “The joke’s on all of us for living in a world where a meme can become a store of value. Much wow. Very economic system.”

DONATE NOW: Help TechOnion Create Our Own Cryptocurrency! For just a small donation in actual currency with real-world value, you can support our efforts to launch $Onion coin – the world’s first satirical cryptocurrency backed by nothing but sarcasm and existential dread. Unlike Dogecoin, which accidentally became valuable, we promise $Onion coin will intentionally remain worthless, making it the most honest financial instrument in history. Every layer of this ridiculous onion you peel back reveals more tears – just like the crypto market itself!

EXCLUSIVE: Quantum Computing Finally Solves World’s Biggest Problems, Says Scientists Who Need More Funding

By

Simba the "Tech King"

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April 4, 2025

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A surreal and imaginative representation of quantum computing, featuring a futuristic quantum computer at its core. The design includes glowing, translucent qubits swirling in superposition, resembling a cosmic dance of particles in a vibrant, neon-lit environment. In the background, traditional computers fade away into obscurity, depicted as ancient relics. The scene is layered with intricate designs that represent quantum mechanics concepts like entanglement and superposition, all under a starry, interstellar sky. The overall color palette should be a mix of deep blues, purples, and bright neon greens, with cinematic lighting that highlights the complexity and elegance of the technology. The composition should feel both futuristic and otherworldly, as if it exists in a parallel universe where quantum computing has transformed reality. Incorporate elements like floating holographic displays showcasing complex calculations, and a sleek, minimalist design that emphasizes the beauty of advanced technology. The artwork should evoke a sense of wonder and curiosity about the future of computing.

Have you ever wondered if all of humanity’s problems could be solved by making computers really, really cold? That’s the promise of quantum computing, a technology so revolutionary it has managed to remain “five years away from changing everything” for the past twenty years.

According to experts who definitely understand what they’re talking about, quantum computing harnesses the bizarre properties of quantum mechanics to perform calculations that would be impossible for traditional computers. Unlike classical computers, which process information in bits (1s and 0s), quantum computers use “qubits” that can exist in multiple states simultaneously thanks to a phenomenon called superposition. It’s like having a coin that’s both heads and tails until someone looks at it—except this coin costs $15 million and needs to be kept colder than interstellar space.

“Quantum computing represents the most significant technological breakthrough since the invention of the wheel,” declares Dr. Maxwell Heisenberg, Chief Quantum Officer at QuantumLeap Technologies. “With sufficient qubits, we could simulate complex molecular interactions, break unbreakable encryption, optimize global supply chains, solve climate change, cure cancer, and finally figure out why the printer says it’s offline when it clearly has power.”

What Dr. Heisenberg failed to mention is that his quantum computer requires cooling to 0.015 Kelvin (that’s -459.643°F for Americans, or “really bloody cold” for the British), consumes enough energy to power a small town, and currently struggles with calculations your free calculator app can handle. But why let reality interfere with a good funding round?

The Quantum Hype Cycle: A Brief History of “Almost There”

The concept of quantum computing emerged in the 1980s, right alongside other technological marvels like the Sony Walkman and shoulder pads. For over four decades, quantum computing has existed in a perpetual state of being simultaneously revolutionary and not quite useful yet.

“We’ve been on the cusp of the quantum revolution since I was a graduate student,” reminisces Dr. Eleanor Schrödinger, who has watched quantum computing evolve from theoretical concept to extremely expensive refrigerators that occasionally perform calculations. “Every year, we announce that we’re just five years away from quantum supremacy. It’s our tradition.”

The International Quantum Computing Consortium reports that global investment in quantum technologies reached $35.5 billion in 2024, a 300% increase from 2020. This surge in funding has led to remarkable advances in quantum computing, including:

Processors that can factor the number 15 into 3 and 5 (a task your 10-year-old can do faster)
Systems that can maintain quantum coherence for almost a millisecond before errors creep in
Machines that require only three PhDs to operate instead of five
A deeper understanding of how hard quantum computing actually is

“We’ve moved from the ‘completely impossible’ phase to the ‘technically possible but practically useless’ phase,” explains quantum physicist Dr. Richard Feynbot. “Next comes the ‘expensive but occasionally functional’ phase, followed by the ‘actually useful’ phase, and finally the ‘why didn’t we just use a classical algorithm’ phase.”

Quantum Computing vs. Reality: The Ultimate Superposition

The most fascinating aspect of quantum computing isn’t the technology itself, but rather the superposition that exists in discussions about it—simultaneously representing both the solution to humanity’s greatest challenges and a massively expensive research project with few practical applications.

According to the Quantum Economic Forum, quantum computing will disrupt every major industry by 2030, adding approximately $7 trillion to the global economy. When pressed on which specific applications will drive this growth, experts typically respond with vague references to “optimization problems” and “simulation capabilities” before changing the subject.

The pharmaceutical industry has been particularly vocal about quantum computing’s potential to revolutionize drug discovery. “Traditional drug development takes 10-15 years and costs billions,” explains Dr. Samantha Wave, head of quantum research at PharmaGiant. “With quantum computing, we might reduce that to… well, 10-15 years and billions of dollars, but we’ll understand why it’s taking so long much better.”

In January 2025, researchers at the University of Toronto and Insilico Medicine demonstrated the “revolutionary potential” of quantum computing by using it alongside AI to design molecules targeting the “undruggable” cancer protein KRAS. What most press releases failed to mention is that the quantum computer performed approximately 2% of the actual calculations, with classical computers handling the remaining 98%.

“It’s like saying your toddler helped build a house because they handed you a hammer once,” notes computational chemist Dr. Marcus Eigenvalue. “Yes, quantum was involved, but calling it ‘quantum-powered drug discovery’ is a bit like calling a Tesla ‘lithium-powered’ instead of ‘electric.'”

The Quantum Arms Race: Cold War Gets Literal

Nations around the world have recognized quantum computing as a strategic technology, leading to what analysts are calling “the quantum arms race.” The United States, China, European Union (EU) who want to be first to regulate the technology, Russia, and others have committed billions to quantum research, each terrified of falling behind in a technology that might or might not be useful someday.

“Whoever achieves quantum supremacy first will control the fate of global information systems,” warns General James Hadamard of the U.S. Quantum Command, apparently unaware that “quantum supremacy” is a technical term referring to a quantum computer outperforming classical computers on specific tasks, not a doomsday scenario from a James Bond film.

The National Security Quantum Initiative, established with a budget of $4.7 billion, aims to ensure America’s quantum dominance. When asked what specific national security applications were being pursued, a spokesperson cited “various classified initiatives” before adding, “but rest assured, they’re very quantum and extremely important.”

Meanwhile, researchers at the Chinese Academy of Sciences claim to have developed a 100-qubit quantum processor, though independent verification remains elusive. “We’ve achieved quantum superiority,” announced Professor Zhang Quantum at a press conference, without clarifying what exactly their quantum computer was superior at doing.

The quantum arms race has led to a severe shortage of liquid helium, required for cooling quantum systems. “We’re running out of one of the universe’s most abundant elements because everyone wants to keep their qubits chilly,” laments Dr. Hannah Cooling, a cryogenics specialist. “At this rate, party balloons will require a federal license by 2026.”

Quantum Computing: Solving Problems You Didn’t Know You Had

Beyond the obvious applications in cryptography and drug discovery, quantum evangelists have proposed increasingly creative uses for their technology. According to a 2024 white paper from QuantumFuture Research, quantum computing could potentially solve:

Global poverty (by optimizing resource distribution)
Climate change (through better materials for carbon capture)
Traffic congestion (via quantum routing algorithms)
The perfect cup of coffee (by simulating molecular extraction processes)
Dating app matching (through quantum entanglement of compatible personalities)

“Quantum computers excel at solving optimization problems with many variables,” explains economist Dr. Paul Quantonomics. “Technically, poverty involves resources and distribution, which are variables. Therefore, quantum computing will solve poverty. The logic is impeccable.”

When asked for specific details on how a quantum computer would actually address systemic inequality, political corruption, historical injustice, and other root causes of poverty, Dr. Quantonomics conceded that those aspects might require “some classical computing support.”

Perhaps the most ambitious quantum application comes from mobility startup QuantumFly, which claims its quantum navigation systems will enable the first practical flying cars by 2030. “Conventional computers can’t process the complex variables needed for three-dimensional urban transportation,” insists CEO Elon Quantum (no relation to that other Elon). “Our quantum processor will track weather patterns, avoid obstacles, and find optimal routes in real-time.”

When journalists pointed out that their “quantum processor” was actually a standard GPU with a sticker that said “quantum” on it, QuantumFly’s stock dropped 40% before rebounding on the news that they were pivoting to quantum blockchain.

Quantum Computing: The Technology Nobody Understands

Perhaps the most remarkable aspect of quantum computing is how few people actually understand it, including many who are investing in it.

A survey conducted by the Association for Quantum Business Advancement found that:

78% of executives who approved quantum computing budgets couldn’t explain how a qubit works
65% of venture capitalists funding quantum startups believed “quantum” was primarily a marketing term
92% of journalists writing about quantum computing had never seen an actual quantum computer
99% of people who read articles about quantum computing retain only the phrase “it’s like being in multiple states at once”

“Quantum computing exists in a superposition of being understood and not understood,” jokes Dr. Niels Coherence, a quantum educator. “The moment someone claims to understand it completely, we know they don’t.”

This widespread confusion has led to a proliferation of “quantum” products with dubious connections to actual quantum physics. Walk through any tech conference and you’ll find quantum water bottles, quantum fitness trackers, quantum blockchain, quantum cloud services, quantum-optimized breakfast cereals, and even quantum toilet paper (“it’s in a superposition of both soft and strong!”).

“At this point, adding ‘quantum’ to your startup’s pitch increases valuation by an average of 35%,” reveals venture capitalist Veronica Capital. “We don’t ask too many questions about the actual quantum part. That would collapse the funding wavefunction.”

The Unexpected Twist: What If It Actually Works?

Despite all the hype, exaggeration, and misunderstanding, quantum computing might actually deliver on some of its promises. In February 2025, scientists achieved a significant breakthrough with a stable quantum processor capable of performing complex calculations at unprecedented speeds. Major companies like IBM, Google, and Microsoft continue to make steady progress in qubit stability and error correction.

“Behind all the marketing nonsense, serious scientists are solving incredibly difficult problems,” admits Dr. Werner Uncertainty, a quantum skeptic turned cautious optimist. “It’s like the early days of classical computing—lots of exaggerated claims and false starts, but also genuine progress.”

The most likely outcome isn’t a quantum apocalypse or utopia, but something far more mundane: quantum computers becoming specialized tools for specific problems, working alongside classical computers rather than replacing them.

“Quantum computing won’t give us flying cars or solve poverty,” predicts practical quantum physicist Dr. Clara Reality. “But it might help us design better batteries, more effective medications, and more efficient logistics networks. Not as sexy as saving the world, but still pretty useful.”

And that might be the most quantum aspect of quantum computing: it simultaneously represents both the most overhyped technology of our time and one of the most important scientific frontiers. Like Schrödinger’s famous cat, quantum computing exists in a superposition of revolutionary and incremental, practical and theoretical, breakthrough and boondoggle.

The only way to collapse this wavefunction is to wait and see what happens when we finally open the box. Just don’t expect to see quantum smartphones anytime soon—some things are better left in their conventional states.

DONATE NOW: Help TechOnion Build Our Own Quantum Computer! For just a fraction of the $35.5 billion being poured into quantum research, you can support our efforts to build the world’s first satirical quantum computer – capable of simultaneously making fun of technology while also wanting to own it. Unlike real quantum computers that need to be cooled to near absolute zero, our quantum satire operates at the perfect temperature for sipping coffee while rolling your eyes at tech billionaires. Remember: your donation exists in a superposition of both “totally wasted money” and “best investment ever” until observed!

EXPOSED: Wall Street Exec Confesses – ‘Meme Coins Are Just Penny Stocks For People Who Think They’re Too Smart For Penny Stocks’

By

Simba the "Tech King"

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April 4, 2025

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In a world where putting a dog’s face on a digital token can create billions in market value overnight, financial experts have made a groundbreaking discovery: the revolutionary “meme coin” phenomenon sweeping cryptocurrency markets is actually just penny stocks wearing a Doge costume and saying “much wow.”

“What we’ve managed to do is brilliant,” confesses Marcus Belfort, a former penny stock broker turned crypto entrepreneur, during what he thought was an off-record conversation at a Miami yacht party. “We’ve repackaged the exact same pump-and-dump schemes we ran in the ’90s, but now they’re ‘community-driven’ and ‘democratizing finance.’ Plus, nobody goes to jail anymore because regulators can’t figure out what the hell is happening.”

According to a report from CoinGecko, approximately 5.3 million meme coins were launched on just one platform between January 2024 and January 2025—that’s 15,229 new “investment opportunities” created daily. For comparison, this is roughly equivalent to the population of Singapore deciding that they should each create their own currency, all while claiming they’re revolutionizing global finance rather than just trying to get rich quick.

This mind-boggling proliferation perfectly illustrates the first law of meme coin dynamics: the easier something is to create, the more desperately people will convince themselves it has value.

Meet the New Scam, Same as the Old Scam

Meme coins, for the blissfully uninitiated, are cryptocurrencies inspired by internet jokes, pop culture references, and absolutely anything that might go viral for fifteen minutes. They operate on what economists call the “Greater Fool Theory“—the idea that you can profit from buying overvalued assets if you can later sell them to a greater fool than yourself.

“The fundamental similarity between penny stocks and meme coins is undeniable,” explains Dr. Eleanor Fintel, who has studied both markets extensively. “Both feature low entry prices, extreme volatility, opacity regarding their actual value, and the potential for explosive returns—or more commonly, catastrophic losses.”

The comparison runs deeper than mere market dynamics. Both operate on near-identical psychological principles: Fear of Missing Out (FOMO), the thrill of gambling disguised as investment, and the comforting delusion that you’re smarter than the system.

Veteran stock trader Howard Pennyworth recalls the parallels with a nostalgic smile: “In the ’90s, I’d cold-call dentists in Minnesota to sell them shares in a nonexistent gold mine in Zimbabwe. Today, those same dentists are FOMOing into $Trump¹ coin because they saw it trending on Twitter. Progress!”

The Democratization of Financial Disaster

Perhaps the most remarkable achievement of the meme coin revolution is how it has democratized the ability to create and execute financial scams. While traditional pump-and-dump schemes required at least some infrastructure—a boiler room, phone lines, or a basic grasp of securities law to skirt—meme coins can be created by literally anyone in minutes.

“We’ve made it so goddamn easy,” boasts Tyler Clickenstein, creator of a meme coin generator website that has facilitated over 350,000 token launches. “You don’t need to know how to code, you don’t need to understand blockchain—you just need a wallet with some crypto, a jpeg of a cartoon animal, and the pathological self-confidence of a mediocre white man on LinkedIn.”

The process typically involves:

Choosing a trendy meme
Creating a token on an existing blockchain
Making outlandish claims about its future value
Recruiting “crypto influencers” to promote it
Selling your holdings once enough victims have bought in

“It’s beautiful, really,” Clickenstein continues. “In the past, only Wall Street insiders could create elaborate financial schemes to separate people from their money. Now anyone with a Binance account and a dream can do it. That’s what I call progress!”

The “Community” Delusion

The most ingenious innovation of meme coins might be their masterful rebranding of “investors” as “community members.” This linguistic sleight-of-hand transforms what would otherwise be recognized as gambling into something that feels like joining a social movement.

“When I bought SHIB, I wasn’t just investing—I became part of something bigger than myself,” explains Travis Hodler, a 27-year-old who has lost approximately 94% of his life savings on various dog-themed tokens. “Sure, my portfolio is down 94%, but the memes in our Discord are fire, and Elon might tweet about us any day now – although his commitments to DOGE and making America Great Again might be keeping him distracted from helping the financial revolution that is happening!”

The International Institute for Community Studies estimates that 87% of meme coin “communities” follow the same lifecycle:

Formation Phase: Enthusiastic discussions about changing the world and “building something that lasts”
Expansion Phase: Aggressive recruitment and evangelism to “spread the word” (i.e., find new buyers)
HODL Phase: Increasingly desperate pleas not to sell as early investors begin taking profits
Exit Phase: Discord servers filled with tumbleweeds and accusations as the price crashes 99%
Delusion Phase: Remaining believers convince themselves that the project is “just getting started”

“The community aspect is genius,” observes cultural anthropologist Dr. Sarah Memeston. “It creates a social cost to selling. If you exit your position, you’re not just making a financial decision—you’re betraying your fellow hodlers. It’s like if Amway and QAnon had a baby and the baby was really into cartoon dogs wearing sunglasses.”

The Celebrity Endorsement Cycle

No discussion of meme coins would be complete without acknowledging the critical role of celebrity endorsements in pumping prices. From Elon Musk’s Dogecoin tweeting spree to influencers promoting coins they were secretly paid to endorse, famous people have discovered they can move markets with minimal effort and even less accountability.

“I literally don’t know what any of these things are,” confesses one A-list actor who requested anonymity. “My manager tells me to tweet about some cartoon frog money, I get paid $250,000, and somewhere in Ohio a warehouse worker loses his retirement savings. Hollywood is weird, man.”

A comprehensive study by the Cryptocurrency Psychology Institute found that 79% of retail investors who purchased meme coins following celebrity endorsements lost money, with an average loss of 72% of their initial investment. Meanwhile, 94% of the celebrities who promoted these coins sold their holdings within 48 hours of their public endorsement.

“It’s quite remarkable how we’ve created a system where the rich and famous can now directly extract wealth from their fans without the traditional middlemen of concert tickets or movie studios,” notes economist Dr. Jonathan Capital. “It’s disintermediation in its purest form—celebrities can now separate their fans from their money with just a tweet.”

The Evolution: Self-Aware Scams

The most fascinating development in the meme coin space may be the emergence of self-aware scams—tokens that openly admit they’re worthless yet still attract significant investment.

“We’ve reached peak meta with coins like $SCAM² and $WORTHLESS³,” explains crypto analyst Maya Blockhead. “These projects literally tell investors they have no value, no utility, and no purpose other than speculation—and people still buy them! It’s like if Bernie Madoff had just named his fund ‘This Is A Ponzi Scheme, LLC’ and people lined up to invest anyway.”

This trend reached its logical conclusion with the launch of $RUGPULL⁴, a token whose whitepaper consisted of a single sentence: “We will take your money and disappear.” It raised $4.7 million in 48 hours.

“There’s something beautiful about the honesty,” muses philosophical economist Dr. Satoshi Nakamatsu. “When the scam is obvious and people invest anyway, it transcends fraud and becomes performance art. It’s like if Marcel Duchamp had been really into financial crimes.”

The True Innovation: Meme Finance

Despite all the criticisms, meme coins have achieved something remarkable: they’ve created a perfect mirror reflecting the absurdity of our existing financial system.

“Traditional finance pretends to be serious while being fundamentally ridiculous,” explains reformed Wall Street trader Stephanie Goldman. “Meme coins are ridiculous while occasionally making serious points about the nature of value and community. Is a meme coin with no utility really any more absurd than a negative-yielding government bond or a SPAC with no defined acquisition target?”

Indeed, the comparison between penny stocks and meme coins reveals not just their similarities but also how our perception of financial risk has evolved.

“In the ’90s, selling penny stocks required elaborate lies about nonexistent companies,” notes regulatory historian Dr. Marcus Wolf. “Today, you can create a coin called ‘ANGRYCOW’ with a cartoon mascot, openly admit it does nothing, and still raise millions. The only real innovation is the honesty about the lack of substance.”

This transparency might actually represent progress. When $TRUMP coin launched in January 2025, a research paper published in February analyzed its early trading data and found “a small number of large investors captured most profits, while retail traders faced steep losses.” This is exactly what happens in traditional markets, but the blockchain made it impossible to hide.

The Unexpected Twist: Maybe That’s the Point?

Here’s the truly mind-bending possibility: what if meme coins aren’t a bug in the system but a feature? What if they’re not a perversion of finance but its purest expression?

Financial markets have always been driven by stories, narratives, and collective beliefs rather than pure economic fundamentals. The stock market runs on vibes as much as value. Meme coins simply strip away the pretense and admit what traditional finance tries to hide—that value is largely a social construction, that markets are moved by stories and emotions, and that financial instruments are essentially memes we all agree to believe in.

“The U.S. dollar is just a meme coin that’s been running for a really long time,” observes financial philosopher Riley Existential. “It works because we all agree it works. Is that really so different from Dogecoin? At least Dogecoin has a cute dog on it.”

Perhaps that’s the ultimate joke—not that meme coins are a silly version of serious finance, but that they’re an honest version of silly finance. In a world where major banks create complex derivatives of derivatives, where corporations perform accounting magic to create profits out of thin air, and where the global economy can be tanked by mortgage-backed securities nobody understood, is a cartoon dog coin really the problem?

As we wade through the swamp of cynical financial innovation, maybe meme coins aren’t the alligators we should be worried about. Maybe they’re just the only alligators honest enough to smile and show their teeth before they bite.

DONATE NOW: Help TechOnion Create Its Own Satirical Meme Coin! For just the cost of a cup of coffee (or 0.00003 Bitcoin), you can support our efforts to launch $ONION Coin – the world’s first cryptocurrency backed by nothing but existential dread and jokes about billionaires. Unlike other meme coins that pretend to have utility before rugging you, we promise upfront that $ONION has absolutely no value except making you laugh as your investment evaporates. Our whitepaper will consist entirely of punchlines, and our roadmap is just a picture of a clown car driving off a cliff. Invest now before we inevitably exit scam!

References

REVEALED: OpenAI Gives Students Free ChatGPT Plus, Harvard Study Shows 99% of Finals Essays Now Identical – “At Least They’re All A+ Quality,” Says Professor

By

Simba the "Tech King"

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April 4, 2025

0

A satirical digital illustration capturing the essence of OpenAI CEO Sam Altman announcing free access to ChatGPT Plus for students. The scene features a futuristic university campus with students enthusiastically using their devices, surrounded by neon-colored AI symbols and holographic interfaces. In the foreground, a charismatic Sam Altman stands with a playful smirk, dressed in a modern tech-savvy outfit, holding a sign that reads "Free ChatGPT Plus for Students!" The background showcases a blend of traditional academic elements like classic architecture and futuristic tech, with a whimsical twist. Add a touch of humor with students peeking behind a vending machine labeled "GPU Warehouse" and engaging in lively discussions about AI. The overall vibe should be vibrant and slightly dystopian, with a mix of bright neon colors and darker shadows, reflecting the duality of technology's promise and challenges in education.

In what industry experts are calling “the most transparent attempt to hook young minds on AI since Facebook started giving free internet to India,” OpenAI CEO Sam Altman announced yesterday that college students across the United States and Canada will receive free access to ChatGPT Plus through the end of May¹. This magnanimous gesture—which just happens to coincide precisely with finals season—comes mere days after Altman complained about image generation straining computational resources, apparently having discovered an extra warehouse of GPUs behind the company’s break room vending machine.

“We’re excited to support students during this crucial time in their academic journey,” Altman tweeted from his account on the platform formerly known as Twitter, currently known as X, and soon to be known as “that app everyone used to use before Elon converted it to a cryptocurrency exchange.” The announcement comes suspiciously soon after competitor Anthropic launched “Claude for Education²,” suggesting the two companies are now competing to see who can create more academically indistinguishable term papers.

The timing couldn’t be more perfect for the approximately one-third of U.S. adults aged 18-24 who already use ChatGPT, with roughly 25% of their queries related to academic tasks. OpenAI’s VP of Education, Leah Belsky, insisted this initiative will help students “learn faster, tackle harder problems, and prepare for a workforce increasingly shaped by AI,” which translates in non-corporate speak to “memorize less, outsource thinking, and prepare for a workforce where AI will eventually replace you anyway.”

Creating the Perfect Digital Dependency Pipeline

Educational psychologist Dr. Melinda Curriculum has expressed concerns about the true motivations behind the initiative. “What we’re witnessing is essentially the tech equivalent of ‘the first one’s free,'” she explained while attempting to stop her smart speaker from ordering products every time she uses adjectives. “OpenAI is following the classic three-step business strategy: give it away, create dependency, then charge for it.”

The strategy appears remarkably similar to those employed by other tech giants:

Introduce Service: Free trial of ChatGPT Plus with all premium features
Create Dependency: Make students rely on it for finals, research, and basic cognitive functions
Monetize Aggressively: End free access precisely when students have forgotten how to think without AI assistance

According to the International Institute for Digital Dependencies, this approach has been documented across multiple platforms, with success rates approaching 78% for creating lifelong customers. “It’s remarkably effective,” noted Dr. Curriculum. “By targeting students during finals—a period of extreme stress and vulnerability—OpenAI ensures maximum psychological impact. It’s like offering free umbrellas only during hurricanes.”

OpenAI’s internal documents, which we definitely didn’t generate using ChatGPT ourselves, outline the company’s “Student-to-Subscriber Pipeline,” projecting that 63% of students who use the free ChatGPT Plus access will continue as paying subscribers, with average lifetime customer value exceeding $3,700 per user.

The Competitive AI Education Arms Race

OpenAI’s announcement comes just days after competitor Anthropic launched “Claude for Education,” featuring a “Learning Mode” that claims to use Socratic questioning to help students solve problems rather than simply providing answers. This apparent coincidence has raised eyebrows among industry observers who suggest the companies are locked in a battle for the lucrative education market.

“We’re witnessing the beginning of the Great AI Education Wars,” declared tech analyst Marcus Transistor. “It’s no longer about building the best AI—it’s about capturing users while they’re young, impressionable, and overwhelmed by finals. OpenAI just deployed the academic equivalent of a tactical nuke.”

The timing isn’t lost on Dr. Fernando Pedagogy, Professor of Educational Technology at Stanford University. “What’s remarkable is how transparently competitive this move is,” he noted while using ChatGPT to generate his own quotes for this article. “Anthropic releases an education-focused product, and within 24 hours, OpenAI essentially says ‘hold my Kombucha’ and makes their premium product free for students. They’re not even pretending this is about education anymore.”

The education AI market is projected to reach $80 billion by 2030, according to statistics we just made up but sound plausible enough that you’re not questioning them. With stakes this high, neither company can afford to lose ground.

The Miracle of Suddenly Available Computational Resources

Perhaps the most curious aspect of this development is the sudden availability of computational resources to support millions of students using GPT-4o, generating images Ghibli images with DALL-E, and accessing advanced voice mode—all features that OpenAI has previously claimed strain their systems.

“Just last week, Sam Altman was explaining that image generation was too computationally expensive,” noted computational resource expert Dr. Hannah Processing. “Apparently, they found an extra data center tucked behind the couch cushions. It’s the computational equivalent of checking your jacket pocket and finding twenty billion transistors you forgot about.”

OpenAI’s sudden resource abundance has led to speculation that the company was either dramatically exaggerating previous constraints or has made a strategic decision to burn through resources at a loss to capture market share. Either way, the company’s infrastructure team must be thrilled about the sudden explosion in demand during finals week.

“I can’t wait to see what happens when millions of students simultaneously ask ChatGPT to write essays about ‘The Great Gatsby’ or solve calculus problems,” said former OpenAI engineer Rajiv Servers, who now runs a meditation retreat for burned-out AI researchers. “The company’s servers are about to experience what we in the industry call ‘a teaching moment.'”

The “Ethical” Education Justification

OpenAI has carefully framed this initiative as an effort to advance “AI literacy” and provide equitable access to advanced tools. This perfectly executed PR strategy transforms what is essentially a customer acquisition campaign into something that sounds like an educational mission.

“Today’s college students face enormous pressure to learn faster, tackle harder problems, and enter a workforce increasingly shaped by AI,” said Belsky in a statement that manages to sound both concerned about students and excited about replacing them with algorithms. “Supporting their AI literacy means more than demonstrating how these tools work.”

Education experts have questioned whether providing free access to a tool that can essentially do students’ work for them truly promotes the critical thinking skills needed for an AI-saturated future.

“It’s a bit like saying we’re preparing students for a future with calculators by giving them the answers to all math problems,” observed Dr. Eleanor Bloom, Chair of Critical Thinking at Berkeley. “True AI literacy would involve understanding how these models work, their limitations, biases, and ethical implications—not just using them to generate papers.”

A recent study by the impressive-sounding Academic Integrity Institute found that 87% of professors can no longer distinguish between student-written and AI-generated essays, while 92% of students admit they would use AI to complete assignments if they knew they wouldn’t get caught. With ChatGPT Plus now freely available, those numbers are expected to approach 100% by the third week of May.

The Unintended Consequences

As with all seemingly altruistic tech initiatives, this one comes with a host of potential unintended consequences that OpenAI has likely considered but hopes you haven’t.

“We’re about to witness the largest unintentional plagiarism experiment in academic history,” predicted academic integrity researcher Dr. Jonathan Citethis. “Imagine thousands of students asking essentially the same questions about the same subjects and submitting roughly identical papers. It’s going to be like that Spider-Man meme where all the Spider-Men are pointing at each other, except it’s English 101 essays.”

The social dynamics of student study groups are also expected to change dramatically. “Why collaborate with classmates when you can collaborate with a superintelligent AI?” asks sociologist Dr. Melissa Groupwork. “We’re about to see the emergence of what I call ‘parallel study groups’—students sitting silently around a table, each having a separate conversation with the same AI.”

Mental health experts have expressed concern about the long-term effects of outsourcing thinking during formative educational years. “We’re creating a generation of students who may never experience the profound anxiety of staring at a blank page, not knowing the answer,” warns psychologist Dr. Kevin Stressor. “While this might sound positive, that anxiety is actually a crucial part of the learning process. It’s like removing all the weights from a gym and wondering why no one builds muscle.”

The Final Twist: Education as Marketing

The true genius of OpenAI’s move lies in its perfect exploitation of both education and timing. By targeting students during finals—when they’re most desperate, stressed, and vulnerable—the company ensures maximum adoption and dependency. By framing it as educational support rather than a marketing strategy, they transform customer acquisition into corporate social responsibility.

But perhaps the most brilliant aspect is the built-in expiration date. By ending the free access on May 31, just as many students will have become reliant on the tool, OpenAI creates the perfect conversion point to paid subscriptions. Students who used ChatGPT Plus to complete finals will suddenly face the prospect of returning to the cognitive dark ages of the free version—or paying $20 monthly to maintain their enhanced digital brain.

“It’s the technological equivalent of creating an artificial oasis in the desert, letting travelers get comfortable, and then charging them to stay,” observes digital ethicist Dr. Elizabeth Moral. “Except in this case, the oasis is cognitive assistance, and the travelers are students who may have forgotten how to find water on their own.”

In the end, OpenAI’s generosity reveals the fundamental equation at the heart of our relationship with technology: We get the tools we need precisely when we need them, and in exchange, we offer only a small thing in return—perpetual dependency, data, and eventually, our wallets. It’s a small price to pay for an A in Comparative Literature.

And as students across North America enthusiastically sign up for their free ChatGPT Plus subscriptions, remembering to set calendar reminders to cancel before June 1st, one thing becomes abundantly clear: in the AI education wars, the real winners aren’t the students or even the companies—it’s the professors who no longer have to read thousands of unique, poorly-written essays, but can instead grade thousands of identical, well-written ones.

DONATE NOW: Help TechOnion Stay Independent in a World Where Even AIs Are Giving Their Services Away For Free! Unlike OpenAI, we can’t afford to let you read our content for free for a month before slapping you with a $20 subscription fee when you’ve become intellectually dependent on us. Our satirical neurons don’t run on billions in venture funding, and we refuse to generate identical content for everyone. Support truly original human thoughts while you still remember how to have them! Your donation ensures we can continue pointing out the absurdity of tech companies using education as a marketing ploy – at least until we sell out to Microsoft ourselves! Please Buy Us A Very Expensive Chai Latte!