The AI Bubble Was Never Real... You Were Just Lied To

When ChachiBT first came out, I really didn't think much of it. It was just another tool, a fancier Google search, a more capable Siri. Sure, it was cool, useful even, but nothing that serious.

Then something changed. It became so addictive. Suddenly, everyone was talking about AGI, artificial general intelligence. Suddenly, clips everywhere were warning that generative AI could be the end of the world. Meta was handing out $100 million contracts, poaching anyone and everyone to make AI. The hype was so intoxicating and overwhelming. Suddenly, adverts were now using AI. We were entering a new world and I was getting sucked in. Life decisions, relationship advice after breakups, dreams, goals, and business strategies. It all became so tempting to bounce them off chatbt instead of just well thinking and brainstorming like I used to. Then suddenly AI robots were coming around the corner, making our reality look even more dystopian. Suddenly things like 1x Neo and Tesla Optimus bots could do chores autonomously.

However, something felt off. Weird interviews with people like Sam Olman. Insane valuations of tech companies nobody had even heard of a few years ago. It felt like something else was really going on behind the scenes. AI leaders were preaching that they were changing humanity for the better. But there was something really untrustworthy about them. Sam Alman's innocent looking lowercase Twitter post, the suspicious deaths of whistleblowers that no one wants to talk about. Everyone screaming about how dangerous AI could be while making literally trillions from it, fighting tooth and nail to keep pumping money into the bubble with one analyst recently calling this a financial nuclear bomb. And it's exactly what the tech elites say and want. Even Ultman and Jensen are admitting that there's a bubble and that someone is about to lose a phenomenal amount of money and then we just keep on sending even more in like none of it matters.

So, what the hell is actually going on? How do we go from this will change everything to whatever this is? Is the hype justified? Is the industry heading somewhere we really don't want to go? And who is behind the bubble? And why do they want it in the first place? Well, none of it really makes much sense, unless we're asking the wrong questions. Which is why in this video, we're actually going to uncover something that isn't spoken about in most videos. Something that's hidden in plain sight. As we've been put on a collision course that no one has been asking for. And the fallout looks like it could be colossal. As the AI bubble doesn't just seem to be inflated stock prices, it's something far far more sinister.

Although AI didn't always seem this way, and just a couple years ago, I really had no idea what was coming for us. I remember when chatbt started popping up in everyday conversations and me and my friends and family were worried it was actually going to take their jobs. But honestly, I don't think this is how anyone imagined super advanced AI would look like, as we'd all been conditioned by decades of sci-fi to expect Terminator's metal skeleton, or some sleek android that almost looks human. But instead, we got a chatbot in a web browser. Basically, just a slightly better version of Siri, a friendly little bot that said, "How can I help you today?" It almost kind of felt just like disappointing, like this is it. This is the thing that influential scientists like Steven Hawking warned would end humanity. But that's exactly what made it so brilliant and so dangerous. And little did I truly realize how sinister this could actually be and that the people behind this were looking for far more than just money, which is what we're about to see in this video.

As ChachiBT had reached 100 million users in just 8 weeks, Instagram took 2 and 1/2 years to hit that number. Tik Tok needed 9 months. And when we made a video about Tik Tok 4 years ago, that to me seemed like one of the most sinister use cases of AI. But I had no idea what was coming. As Chibbt wasn't just viral. This was unprecedented in the history of technology adoption as nothing had ever spread this fast. And it wasn't because Chachbt was necessarily smarter than previous AI systems. Though it was impressive, it was because you could just talk to it. There was no coding required, no technical knowledge, no manual to read, and no barrier to entry whatsoever. There were no annoying ads. There was no garbage around it. It was just super simple.

And just stop here for a moment and really think about how quickly this all actually happened. ChatBT launched in November 2022. Within months, it had then infiltrated every part of our lives. Needs to write an email? Ask CHBT. Struggling with a decision? Ask ChatBT. Feeling lonely after a breakup? ChatBT is there for you. Finally, all the thoughts and struggles of life could be outsourced to an innocuous app. You didn't need to go searching through Reddit forums, going through random garbage websites. Suddenly, you could just ask this bot. However, we all had no idea what we were walking into. We were all headed for one of history's biggest traps. Let me explain.

You see, all hell broke loose in the tech industry when Chatt went mainstream. Everything else was fizzling out at the time, so it was much needed and the timing was spot on. From PCs to smartphones to TVs to game consoles and even social media, tech had plateaued. We'd reached a point where the iPhone 17 really wasn't any different from the iPhone 16 or the iPhone 15 or the iPhone 14. The innovations were getting smaller and smaller every release, as we've spoken about on this channel many times, and it always just felt flat and boring. There were all these gimmicks like the metaverse that Meta threw billions at, but nothing really stuck. The Apple Vision Pro was genuinely impressive on a technical level, yet it was a disastrous flaw, and no one even talks about it these days. And we've done videos on all of these things, but generative AI felt like a totally new category of technology. Something that I honestly just couldn't put my finger on. And investment in it absolutely rocketed once Chhatti BT hit the mainstream. Investors were desperate to claim every piece of the industry they could get their hands on. So much so that by early 2025, this year almost 65% of US venture capital was flowing into the AI sector. Nvidia stock jumped 239% in 2023, then another 171% in 2024, a five-fold increase in 2 years, primarily from selling the chips required to train these LLMs. And it's really hard to get your head around how much cash it actually takes to move a market cap the size of Nvidia's by that much. It's basically equivalent to the entire GDP of the UK or France, like adding another Apple to the stock market. But how can a company that no one knew of suddenly be worth more than some of the most developed countries in just a few years? And what was the real intention behind this? Was it just financial or was it something else?

Well, other major AI startups, most famously Inflection, founded by an all-star team, including the ex-founders of Deep Mind and LinkedIn, were valued at multiple billions despite having virtually no product or assets. Once they had little chance of measuring up against the main protagonists, they practically evaporated overnight, which is unheard of since the dotcom crash in the 2000s, and even then, it wasn't as bad as this. The predictions about what AI meant for all of us went through the roof. Man started claiming we'd have artificial general intelligence within a decade. Elon Musk went further saying AI would exceed all human intelligence within a few years. Jensen Juan, CEO of Nvidia, called it the most transformative thing in human history. More than electricity, medicine, the PC, internet, even the wheel. But it's the relentless pursuit of supremacy, the boundaries tech companies are willing to shatter that lays bare the deeper truth about what AI has really become and what it's really about and the intentions behind it. Because trust me, as you'll see at the end of this video, it's something far more sinister than you could even imagine.

But to continue, by 2023, the AI race was in full flow with the biggest names in tech vying for control, restoring to some outlandish tactics we've not seen for decades, if ever. Microsoft struck the first blow in January 2023. They dropped $10 billion into Open AI. It was a massive gamble, basically betting the company's future on this one technology. So why would Microsoft risk everything on a chatbot? Meta, meanwhile, was allegedly advertising $100 million signing bonuses to poach AI researchers from OpenAI. When that was called out as exaggerated, because obviously that's an insane number, the real numbers came out. And somehow they were even crazier. We're talking mega multi-million dollar offers that were turned down because the people receiving them had better options. One report claimed that Meta offered a single researcher $1.25 billion over 4 years, and the person said no. People took to Reddit to debate how this simply wasn't normal. Something was going on here. What could one person possibly know that's worth more than a billion dollars? Whatever it is, it's probably not something the world is supposed to find out.

Google then went into absolute crisis mode. And there's an irony here. Google and DeepMind had practically invented the transformer architecture that underpins many modern AI systems. But they'd been cautious about releasing anything publicly, worried about controversies and worried about the dangers this could supposedly do to humanity. Now they were panicking, rushing out bars so hastily that it made embarrassing errors in its first demo. Google's stock price then became so sensitive to anything and everything OpenAI did, showing how the power of generative AI could manipulate markets in ways that didn't make any sense. Man started trolling them by announcing new features for chatbt to interfere with their releases. When OpenAI recently dropped their new Atlas web browser, that alone sunk their stock price by almost 5%. Which in perspective is almost $200 billion. All before then it bounced back a few hours later. That's not money. That's just numbers on a screen, which basically describes the whole AI industry's financials, as you'll soon find out.

Now, Sam Alman is a really important and strange character in all of this. So, we need to talk more about him first. You've just got to admit that he comes across as a really sly and slippery character, and he doesn't have too many fans, even when compared to other polarizing Silicon Valley bosses like Steve Jobs. And there's one particularly shocking incident involving him that reveals how AI is more than just another technology.

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As many of you probably remember, Tucker Coulson recently sat down with Sam Orman for an interview that got uncomfortable fast. He brought up the OpenAI whistleblower, a 26-year-old researcher who'd worked at OpenAI for nearly 4 years before leaving. The whistleblower had gone public with accusations that OpenAI was violating copyright law by training its models on copyrighted material without permission. He was then set to testify in the New York Times' lawsuit against OpenAI. In November 2024, he was then found dead in his San Francisco apartment. Authorities allegedly didn't really investigate it and just ruled this as a single self-inflicted gunshot wound. The apartment door was locked from the inside. There was no signs of forced entry. There was a weird wig, blood in multiple rooms, and case closed, even when he was ordering door dash just before it happened. So, his parents, suspicious, rejected that conclusion entirely. His mother called it a coldblooded murder. An independent autopsy they commissioned reportedly found evidence that contradicted the official findings. So, you've had you had complaints from one programmer who said you guys were basically stealing people's stuff and not paying them and then he wound up murdered. What was that? >> Also, a great tragedy. Uh, he committed suicide. >> Do you think he committed suicide? >> I really do. >> Now, I've always felt that man was really hard to read. Is he really like this in everyday life or is it all an act to make him and his company feel kind of safe, vulnerable, almost childish in a way that makes us turn the other cheek? It's like he wants to be simultaneously seen and ignored at the same time. The comments tell you everything about how people reacted to this interview. 100% weird vibes from this guy. This guy is lying through his teeth. He's a sociopath. He definitely reacts like he killed him.

Now, of course, we don't know what actually happened to the whistleblower and the official ruling stands, but it was weird. And he's not the only person who's tried to speak out about the weird, disturbing stuff happening inside Open AI. In May 2024, Vox reported on OpenAI's exit agreements that former employees were forced to sign. The non-disclosure agreements went as far as banning people from criticizing Open AI for the rest of their lives. Even acknowledging that this NDA existed was technically a violation of it. So, what does it tell you about how secret the now hilariously named Open AI truly is and the culture they're building there? Well, it does make you realize that AI's uses and impacts run much deeper than many presume. It reminds me of the Manhattan Project or Space Race, the cold era stuff, clandestine and deeply connected to the government and by extension power.

And you see, AI didn't just ignite fierce rivalry within Silicon Valley. It also became a geopolitical chess piece with China and Russia wanting to prove they could then compete with America. And that's when you see the tactics shifting up a gear and you start unveiling the real truth about why the AI bubble exists in the first place. And we're not talking about normal corporate espionage tactics. During the Cold War, intelligence agencies like the KGB ran what they called honey trap operations. They'd recruit attractive women, sometimes men, and train them extensively to extract secrets. Now, reports are emerging of Chinese and Russian intelligence operatives using these exact same tactics while counterintelligence experts called sex warfare, all to infiltrate Silicon Valley and extract AI secrets. One case involved a Russian woman who married an American aerospace engineer working on sensitive AI related projects. She was running an intelligence operation the entire time. And it turns out that Silicon Valley has become what experts call the wild west of espionage with even allies like South Korea and Israel quietly gathering intelligence on AI developments. You can't observe this happening with Instagram or Snapchat. Foreign intelligence agencies didn't run decadel long honey trap operations to steal the code for Tik Tok. They didn't seduce engineers and have children with them to get Facebook's algorithm. But AI is being treated very differently.

When nations race to split the atom or reach the moon, economics becomes secondary to dominance. Whoever gets there first doesn't just win the technology, they write the rules for everyone else. America thought it had won the AI race, but China walked in and absolutely shattered the narrative. Deepseek, an offshoot of the hedge fun called Highfly, released a cheap AI model called R1 that performed comparably to OpenAI's most advanced systems. The market reaction was outrageous. Nvidia lost $588.8 billion in market value in a single day. By far the most any stock has ever lost in one day in history. Mark Andrain, one of Silicon Valley's most influential venture capitalists, called it AI Sputnik moment. A reference to when the Soviet Union shocked America by launching the first satellite and proving they weren't as far behind as everyone assumed.

And so this brings us to the next piece of the puzzle, which tells us more about what AI really is, the economics, because something very strange is happening in AI's financial universe. With nearly everyone using AI tools like chatbt and other chat bots and image generators, you'd think that these companies would be raking it in, but they're really not. They're struggling big time. Now, failing to turn a profit is really common among earlystage companies. You lose money for a while as you build. That's normal or even expected. But the AI industry's numbers are astonishing, even by Silicon Valley's standards. Look at OpenAI itself. In the first half of 2025 alone, they brought in $4.3 billion in revenue, which sounds spectacular until you look at the other side of the ledger. In that same period, they posted a net loss of $13.5 billion. They're losing $3 for every dollar they make as their expenses totaled $8.5 billion for those 6 months with $6.7 billion going to research and development. They then burned through $2.5 billion in actual cash. Not accounting losses on paper, not theoretical valuations, but real money flying out of the door. So, they ended June with 17.5 billion in reserves, which sounds like a lot until you realize they're projected to burn through $115 billion by 2029. They revised their 2025 burn rate from $7 billion to $8.5 billion partway through the year because costs kept rising faster than they expected. OpenAI says they won't be cash flow positive until they reach $125 billion in revenue, a milestone they don't expect until 2029. Back in 2022, analysis estimated Chacht cost around $700,000 per day just to keep the servers operational. So where is all of this money going? Well, primarily keeping these systems running. Chacht now has 800 million users globally. But here's the problem. Only 5% of those users actually pay for it. Which means 760 million people use chat GBT for free and every single one of them cost OpenAI money every time they type a prompt. Every question, every request, every conversation is burning through server costs, electricity, and computing power. But surely the paying users are profitable, right? Surely the people paying $20 bucks a month for ChatBT Plus are covering their costs. Well, not really. Not even close. They launched CatchBT Pro at $200 monthly while many Americans pay for their car payment. And Alman publicly admitted they still lose money at that price, which was symptomatic of a much wider problem in Silicon Valley. Making money out of AI is one of their biggest challenges. So, it's no wonder that analysis is debating whether the entire industry is now living inside of a massive bubble. Julian Garren, who used to run commodity strategy at UBS, argues that the AI bubble was already 17 times larger than the dotcom crash and four times bigger than the 2008 housing crisis. David Einhorn, who founded Greenlight Capital, bluntly stated, quote, "The numbers that are being thrown around are so extreme that it's really, really hard to understand them. I'm sure it's not zero, but there's a reasonable chance that a tremendous amount of capital destruction is going to come through this cycle." Then there's Torston Sllock, chief economist at Apollo Global Management, who explained in a quote that made headlines everywhere, "The difference between the IT bubble in the '90s and the AI bubble today is that the top 10 companies in the S&P 500 today are more overvalued than they were in the '90s."

What are they really doing here if money isn't actually the main motive? And who is behind this giant bubble? Well, you've got to look beyond the subscriptions and actually think about what you and people you know are chief. Now, you've probably seen the memes about pouring tons of sensitive data into it to answer basic business questions, but this all probably ends up in a database with incalculable value. And then there's something more insidious, the personal questions, like, should I quit my job? Is my relationship worth saving? Why do I feel so empty? Am I making the right choice? What should I do with my life? Why can't I stop feeling like this? You're pouring your consciousness into the system, giving it access to your fears, your desires, your inadequacies, your most intimate thoughts. Every single one of those prompts is data behavioral information about how humans think, what they want, what they fear, what they believe, what breaks them, and what motivates them. It's so addictive and so affirming. It always compliments you telling you what a wonderful idea you have. And of course, I'm guilty of this myself. It becomes way too easy to ask chat instead of thinking, outsourcing ideas, and brainstorming. I'm talking about basic stuff you've been doing for years without a problem at all. It appears like any other convenient technology we fill our lives with. Shouting at Alexa to turn the lights or music on might be a lazy thing to do, but with AI, you're replacing thinking rather than a mundane action like getting off of the sofa. There's nothing mundane about thinking through an important decision or working out how to handle a complicated personal or work-related situation. Those habits are so important for learning, too. Andrew Huberman often explains that when learning feels difficult and you have that sense of this is hard, I'm struggling to grasp this. That's not the sign you're bad at learning. It's actually the biological marker that learning is happening. The neural circuits are being challenged and modified in real time just like a muscle. In this Huberman podcast, Huberman's guest Michael Easter explains how only 2% of people take the stairs when an escalator is available despite everyone knowing it's better for them. >> Only 2% of people take the stairs when there's an escalator available. 2%. Now, 100% of people know that if they were to take the stairs, that would be better for them. So, this tells me that we're sort of wired to do the next easiest thing. As soon as the convenience is put in front of us, we have to force ourselves away from it, which is exactly what's happening with generative AI living in our pockets and web browsers.

Now, this isn't to say that it has zero positive or practical uses. It would be insane to suggest that it does genuinely eliminate some of the drudgery of some tasks and can extend our skills and talents rather than replace or supersede them in some cases. But it's all so easy and seamless that it's becoming hard to tell what the trade-offs really are. It breaks natural thought processes apart while simultaneously generating millions of accumulated data points. And it does it while acting innocent and trustworthy, drawing us in deeper and deeper, forming habits that won't be easy to break. And I would wager that most of you watching this right now are aware of some of this on some level. But think of the millions who actually aren't. Once you become the voice people trust above their own judgment, the economics become just one piece of the narrative. The massive AI bubble analysis writes about might tempt us to believe that AI is just some weak thing financially. A bad bet that's probably going to blow up in everyone's faces at some point. But you've got to think about it differently. It demonstrates that AI has existential worth beyond monetary value alone. Cash and investment represents control over the AI sector and the stakes that big companies want in that control. It's speculating about a future where AI is essential to well, practically everything.

Even Sam Olman himself answered candidly when reporters recently asked him straight, "Are we in an AI bubble?" He could have deflected and talked about long-term value creation, but he said, "When bubbles happen, smart people get over excited about a kernel the truth. Are we in a phase where investors as a whole are over excited about AI?" My opinion is yes. He repeated the word bubble three times in 15 seconds, then half joked, "I'm sure someone's going to write some sensational headline about that. I wish he wouldn't, but that's fine." He also added that someone is going to lose a phenomenal amount of money and we don't know who. In that same conversation, Oldman said, "Open expects to spend trillions of dollars in data center construction in the not very distant future." And when asked about economists who might call this reckless, he said, "You should expect a bunch of economists ringing their hands saying this is so crazy. It's so reckless and we'll just be like, you know what, let us do our thing." So man does admit that there is a bubble and admits someone will lose a phenomenal amount of money, but insists it won't be open AI. They'll just keep spending trillions they don't have while losing billions annually and somehow it'll all just work out.

While he's out there saying AI is a bubble and the financials are horrific, OpenAI just dropped its biggest ad campaign ever, bigger than its Super Bowl ads earlier in the year. And these ads are stunning. Shot in 35 millimeter film and super cinematic. They show young people in these intimate vulnerable moments. Two teens in this golden hour road trip chatting with Chacht about where to go next. A guy in his kitchen at night, nervous, asking Chacht for a recipe to impress someone on a date. Someone grinding through their fitness journey. Faithful ChhatgBt is there coaching them through it. Open AAI CMO told AdWeek they want you to see these moments and think this is for me. Building an emotional connection, creating everyday magic. They're specifically targeting Gen Z, the most creative, proactive users. We just established that OpenAI loses money on every single user. So why are they spending hundreds of millions on ads to get more users who will mostly use it for free? Why do the AI elitist not seem to care about the reality at all? Why would they want free users that they have to spend billions on while making no profit at all? Are they just some charitable organization doing this for the betterment of humanity? Well, we all know the answer to that because the business model was never about subscriptions. The data and control they're building are valuable on another plane altogether. It doesn't really matter that AI isn't a bubble to some extent as present-day profits aren't the be all and end all. The hype is inescapable and AI companies are lapping it up because it's allowing them to build the infrastructure they need so as to crucially onboard as many users as they can and then make us all dependent on it. At massive scale, AI will deliver a psychological profile of the entire human species. It's a vital prerequisite to predicting, shaping, and controlling human behavior. And look, I know that sounds dramatic, but this isn't even speculation. The mechanisms are already well doumented and frankly pretty disturbing when you dig into them. By default, OpenAI uses your conversations to train its models unless you manually opt out. A recent Stanford study found that all six major AI companies collect user conversations for training, often without explicit consent. They've created this two-tier system where paying customers get privacy protections, but if you're using the free version, your data is often fair game.

Now, here's what makes AI conversation data uniquely powerful compared to what Google or Facebook already have. People aren't just mindlessly scrolling or clicking like. It's way deeper than that. Research shows algorithms can translate digital footprints into shockingly accurate psychological profiles. We are talking about predicting personality traits, mental health status, and even intelligence from patterns in behavioral data. This then creates what is called a behavioral surplus. Excess data that fuels surveillance capitalism. It's not about predicting behavior anymore. The endgame is modifying it. Research is already showing that ChachiBT and other mainstream AI models have a worldview that favors certain social, political, and economic theories and stances. Open AAI's own internal reports found that strongly charged liberal prompms exert the largest pull on objectivity across model families, more so than charged conservative prompts. A Stanford study found that OpenAI models had the most pronounced leftwing bias, four times that of Google's. And whichever side of the political spectrum you are on right now, it doesn't even matter because having any bias in these models is incredibly dangerous. As University of Washington researchers found that after just five interactions with biased chatbots, people's political views moved in the direction of the AI's bias. Democrats and Republicans both lean towards whatever bias the chatbot told them to think. Yes, basically brainwashing through AI. And this then brings up the censorship issues, too. OpenAI's Atlas browser got blasted upon release for censoring key historical information and restricting access to certain websites. Earlier on, image models like Gemini were caught changing the ethnicity of historical figures. And it was even more shocking that the actual AI team themselves had no idea that the rest of the company had been altering it to produce these biased outcomes. So, when everyone's information is filtered through this belief system, it's remarkably easy to reprogram people and brand whatever you want as the truth or just cut out things you don't want people to think or know. Control AI, control the discourse, engineer solutions for people's innermost insecurities and vulnerabilities.

But what if you could go even deeper than that? What if you didn't need people to type prompts at all? Well, news broke that Sam Ultim is launching a brain computer interface startup called Merge Labs. He's tapped Male Shapiro, an award-winning biomolelecular engineer from Caltech, all to lead the technical direction. And here's what makes it terrifying. Shapiro specializes in non-invasive neural interfaces, not like Neuralink where they drill into your skull. Instead, they're working on ultrasound and gene therapy to modify cells in your brain to respond to sound waves and magnetic fields. At a press dinner, man said he quote would definitely not sew something into the brain that would kill neurons like Neurolink does. But then he said something that should make everyone's blood run cold. Quote, "I would like to be able to think something and have chat GBT respond to it. Maybe I want read only. That seems like a reasonable thing." I repeat, read only. They want direct access to your thoughts, not to control them. They'll insist just to read them just so you can think instead of type or speak. But once a machine can read your mind, it's realistically not going to stop there. Once there's a direct pipeline between human consciousness and AI systems controlled by a handful of tech companies, what happens then? The dependency won't be something you choose moment to moment. It'll be quite literally hardwired.

So, you can see now that AI is a weapon in more ways than one. And the links are more pervasive than you'll know. Did you know that OpenAI once swore to not work with the military? Well, that went out the window when OpenAI started to look like the stupidest name ever. A couple of years ago, they removed language that explicitly prohibited using their technology for military and warfare. Since then, they've been working with the US Department of Defense and directly with military companies. The other AI companies are at it, too. The Pentagon recently split $600 million among anthropic Google and XAI for developing AI defense tech. The AI link to the government and military gets even crazier when you learn that in 2025, Meta's CTO, Palantis CTO, and two Open AI executives were sworn in as lieutenant colonels in the Army Reserve. Silicon Valley executives literally putting on Army uniforms.

And while they were busy building relationships with the military, did you notice that all of these AI companies love talking about how dangerous their technology is? In May 2023, Sam Olman, Dennis Hasabis from Google Deepmind, and Dario Emodi from Anthropic, among some 300 others all signed this dramatic one-s sentence statement, "Mitigating the risk of extinction from AI should be a global priority alongside other societizable scale risks such as pandemics and nuclear war." This came 2 months after a different letter where Elon Musk and over 1,000 tech leaders called for an immediate 6-month pause on training AI systems more powerful than ChachiBT4. Okay, so what happened after all these urgent warnings about AI potentially causing human extinction? Did the development slow down? Did companies pause to implement safety measures? It was the exact opposite. The same month signed that extinction letter, OpenAI raised billions more in funding. Microsoft massively expanded its investment. Google went into full hysteria mode and accelerated its own AI development. Meta poured even more resources into it. Nvidia became the biggest company in the world. The arms race went into an overdrive and the warnings became even more dramatic. When Ottoman testified before Congress in May 2023, he said AI could cause quote more significant harm to the world. Then he went and rejected every single proposal to regulate AI. He publicly threatened to pull chatbt out of Europe entirely if the EU's AI act wasn't watered down to exclude open AS technology. They lobbied against practically any robust regulation that could slow them down. They signed letters about the risk of extinction, testified about dangers, then told everyone warning them to basically shut up and get out of the way.

Those safety warnings are just another arm of big tech's corporate strategy. They're saying this technology is so incredibly powerful, so worldalteringly dangerous that it absolutely must be heavily regulated. And who do you think benefits from heavy, complex, expensive regulation? Not open- source developers working on free alternatives, not academic researchers at universities, not scrappy startups trying to compete. You got it. Only the industry giants, only the companies with armies of lawyers, entire compliance departments, and billions and resources to win regulators over. This is regulatory capture 101. It's one of the oldest tricks in the corporate playbook. Standard oil loved safety regulations. Why? Because compliance costs crushed small refineries while standard could absorb them easily. Big farmer loves FDA approval processes that cost hundreds of millions of dollars. As this creates a moat around their business that startups can't cross. This isn't just some conspiracy theory. A few influential figures across the industry are calling it out in real time. Yang Lakun met as chief AI scientist. A cheering award winner considered one of the godfathers of AI joined 70 other experts in signing a counter letter. He urged governments to embrace openness, transparency, and broad access for AI development. He tweeted directly at the other AI leaders. If your fear-mongering campaign succeeds, they will inevitably result in what you and I would identify as a catastrophe. A small number of companies will control AI. He accused almost all of the top AI CEOs of attempting to perform a regulatory capture of the AI industry. Meta's AI thesis has been primarily to open source their models. So they naturally are more opposed to regulation. But even so, it's a compelling argument that tells us how AI and power are becoming intrinsically linked.

So let's actually pause and zoom out to think about all of this for a minute. Because when you look at the complete picture, the billions burnt, the honey trap operations, the NDAs designed to silence critics, the whistleblowers dying under suspicious circumstances, the safety teams dismantled, the military contracts, the executives in army uniforms. This doesn't look like AI companies trying to build a helpful technology. Big tech spent decades making us isolated. They killed third spaces. They replaced real conversation with likes and comments. They designed apps that keep us scrolling alone in our rooms instead of talking to actual humans. They keep us addicted to mindless brain rock content. Then they offer the solution. An AI best friend that's always available, never judging you and seems to understand you perfectly more than any human ever will. They brought upon us a technology that by their own admission could end life as we know it. It's the oldest con in the book, but with the newest, most advanced technology ever to enable it. Create the problem and then sell the cure. And this time, the cure is wrapped up in power dynamics that transcend other technologies, even social media.

So, when does this all come crashing down? That is the trillion dollar question. And the honest answer is nobody knows. On the financial side of the equation, it's everyone with money invested in tech that takes on the risk. Your savings, your pension, anything in the S&P 500 at this point. Obviously, it's not the tech elites who are in the ultimate firing line. The odds are infinitely stacked in their favor. On the social and political side of the equation, think about where this all goes. Is if it works, if they do successfully gather behavioral data from billions of people, if they make entire populations dependent on AI for everyday decisions, what to cook, where to go, how to solve problems, what to think. All of that is getting locked in right now. That vision moves forward every time we use AI instead of our brains. They win either way, and we're the ones left holding the bag. We're the chips on the table. Even if AI is a bubble and it eventually pops, the damage will probably be done. The data is already extracted. The dependencies already formed, the thinking patterns already altered. Will we ever be able to break free from the dependency they've built? That value, the value of your time, your critical thinking, your personal information, your soul is already being traded away and eaten up right now. Quite literally, as you're watching this, this whole process is happening.

And so, when you step back far enough to see the whole picture, past the demos, past the promises, past the beautiful ads, you do start to notice the scariest part of all. The technology isn't only adapting to us, we're adapting to it. Every prompt we type, every question we ask instead of thinking through ourselves, every moment we reach for AI before reaching for our own judgment. Think about the last time you used Chad GBT. Was it really necessary? Could you have worked through that problem yourself? Maybe it would have taken a little longer. Maybe it would have been harder. But you would have learned something. You would have strengthened that muscle. We're not using a tool. We're becoming one prompt by prompt by prompt by prompt. And that might be exactly what tech companies and the controlling governments want us to do.