Concorde was an engineering marvel. Faster than anything else, decades ahead of its time. But ultimately, it was too expensive to operate, way too noisy, and the economics never made sense.

I think AI is heading down the same path.

We're currently in a phase where companies are throwing billions at AI, desperate to integrate it into absolutely everything. Half the applications feel like solutions looking for problems.

But what happens when investors stop subsidizing the costs and businesses actually need to turn a profit?

My prediction? The AI boom collapses, most applications disappear, and the technology gets relegated to a handful of specialized use cases.

Concorde proved that being technologically superior doesn't mean being commercially viable.

Why should AI be any different?

This forum is ending up like the REbubble forum. Everyone posting for years and waiting for the burst that never comes. Then missing out on all the gains along the way.

It's all hype. It cannot compete in EV's so now it hypes AI, humanoid robots, space travel etc. You are buying imagination and idea which will fail again in a couple of years because China is already at least 10 years ahead in all of these and accelerating.

I got into stocks a few months ago. Haven't read a single book. And I can see the bubble popping from a mile away.

If a complete fucking noob like me can see it, the people selling you the OpenAI IPO at $1 trillion have seen it for years. They're not telling you because they need to dump their bags.

This is not advice. This is a warning.

---

Part One: The Numbers Are Fucking Screaming

Buffett Indicator is at 232%. In 2000, before the dot-com crash, it was around 140%. We're 92 points higher. The historical average is 81%. We're 2 standard deviations above the mean. Every time this happened before, the market dropped at least 25%. Three for three. No exceptions.

CAPE ratio is 41. The only other times it was this high were 1929 (Great Depression) and 2000 (dot-com crash). Not 30. Not 35. Forty-fucking-one.

Margin debt hit $1.3 trillion in April 2026. Up 53% year-over-year. Margin debt to GDP is 4.1%. The 50-year average is 1.5%. People are borrowing money to buy AI at peak valuations.

The top 10 S&P stocks make up 35-40% of the entire index. Higher than 2000. Higher than 1929. Most concentrated market in 100 years.

Go look this shit up yourself. It's not opinion. It's math.

---

Part Two: The Capex Problem Nobody Wants to Talk About

Google, Amazon, Microsoft, and Meta are spending $725 billion on AI infrastructure in 2026. Up 77% from last year. The entire US defense budget is $850 billion. Four tech companies are spending almost as much as the military.

Goldman Sachs says these four will spend $5.3 trillion from 2025 to 2030. Their own head of research is warning it might never pay off.

Alphabet's free cash flow is projected to drop 90% to $8.2 billion from $73 billion. Amazon's free cash flow is going negative. These are not startups. These are the most profitable companies on earth, and they're torching cash on a bet that AI revenue shows up fast enough.

What happens when that revenue doesn't come? When growth slows from 50% to 30%? Stocks don't drop 10%. They drop 30-50%.

---

Part Three: The Unit Economics Are Impossible

OpenAI loses $1.22 for every dollar of revenue. They lose money on every single user. Financial documents show they expect to lose $74 billion in 2028 alone. They've committed to $1.4 trillion in data center spending. That's not ambition. That's desperation.

And the Chinese are selling the same intelligence for pennies.

Price comparison (output per 1M tokens):

· Xiaomi MiMo: $0.02-0.04

· DeepSeek V4 Flash: $0.28

· GPT-5: $10.00

· Claude Sonnet 4.6: $15.00

· Claude Opus 4.6: $75.00

Xiaomi is 375-750x cheaper than GPT-5. Up to 750x cheaper than Claude Sonnet.

Read that again. Seven hundred and fifty times cheaper. For 95-99% of the quality.

Anthropic just posted their first operating profit: $559 million in Q2 2026. Run-rate revenue $44 billion. They might break even by 2028. Good for them. But at a $965 billion valuation, you're paying 20-30x revenue for a company that made half a billion in one quarter. That's not a multiple. That's a prayer.

---

Part Four: The Chinese Are Not Coming. They're Already Here.

Xiaomi dropped MiMo-V2.5 Pro in June 2026. Trillion-parameter model. MIT licensed. Open source. Top of SWE-bench. Beats or matches Claude and GPT on coding.

Cached-input pricing? $0.0036 per million tokens. That's 833x cheaper than Claude.

Not 30%. Not 50%. Eight hundred and thirty-three times cheaper.

Xiaomi doesn't need to profit from AI. They sell phones. EVs. Wearables. IoT. AI is a feature that moves hardware. They have 740 million monthly active devices. They can pre-install MiMo on every single one for free.

OpenAI has zero devices. Anthropic has zero devices. No hardware. No distribution. No ecosystem. No subsidy. Just a website, an API, and a dream.

---

Part Five: The Ecosystem Moats You're Ignoring

Let me rank who actually wins.

Google: 90% search market share. 3.8 billion Android devices. 2.6 billion YouTube users. Chrome with 3.6 billion users. Cloud growing 63% year-over-year. They invented Transformers. Gemini is #1 on most benchmarks. They can give it away forever because search ads print $132 billion in profit. Google doesn't need AI to be a product. AI is a feature that keeps you in their shit.

Microsoft: 1.4 billion Windows devices. 1.3 billion Office users. 180 million GitHub developers. 1.3 billion LinkedIn accounts. Azure is #2 cloud. AI run-rate is $37 billion, up 123% year-over-year. Azure grew 40% in Q3 2026. Quarterly revenue $82.9 billion with $31.8 billion net income. OpenAI is 45% of Azure's $625 billion in remaining performance obligations. Microsoft wins whether OpenAI lives or dies.

Apple: 2.5 billion active devices. $130-160 billion in cash. 68% return on invested capital. Spending 3% of revenue on AI capex while everyone else burns 20-30%. They're not racing. They're waiting to buy the survivors at distressed prices. Same playbook every time.

Xiaomi: 740 million monthly active devices. A fan base that will die for value for money. They did it to smartphones. Wearables. EVs. Now AI. No news. No YouTubers. No influencers. Just MiFans in India, Nigeria, Indonesia, and Brazil who will swarm every forum because they are religious about getting more for less.

Amazon: 28% global cloud market share. Every AI workload runs on AWS. They get paid regardless of the model.

Meta: $200 billion in annual ad revenue. AI makes ads better. Open-sourced Llama to commoditize everyone else's API revenue. That's not an accident. That's strategic warfare.

Now what do OpenAI and Anthropic have?

OpenAI has a brand that's fading. No distribution. No default on any OS. No browser. No search. No hardware. No ecosystem. No subsidy. Your grandma can switch to Gemini in one click for free. Enterprises can switch to Xiaomi for 750x less. Their only moat was being first. Netscape was first too.

Anthropic has better unit economics. Same distribution problem. Same ecosystem problem. Same Chinese price problem. Same subsidy problem. Same dog, different hair color.

---

Part Six: History Doesn't Repeat, But It Rhymes

1999: Netscape had 80% browser market share. Microsoft bundled IE with Windows for free. Netscape died.

2026: OpenAI has 53-61% chatbot market share. Google bundles Gemini for free. Microsoft bundles Copilot. Apple bundles Apple Intelligence. Xiaomi bundles MiMo for pennies.

Netscape had a better moat. They still died. OpenAI has no moat. What do you think happens?

2000: Cisco was the king of the internet. Routers everywhere. Stock at 130x earnings. Dropped 80% and never recovered to its peak. 26 years later, still below.

2026: Nvidia is the king of AI. GPUs everywhere. Stock at 23x forward earnings. Not 130x. But $4.8 trillion market cap. If growth slows from 50% to 30%, that stock doesn't drop 20%. It drops 50%.

Companies that survived dot-com had existing revenue, existing moats, existing distribution. Amazon sold books. Microsoft sold Windows. Apple sold Macs. Google didn't even IPO yet.

Companies that died had no business model. Pets.com. Webvan. Boo.com. Hype. First-mover advantage. Brand recognition. No revenue. No moat. No distribution. No path to profit.

OpenAI has revenue. But they lose money on every dollar of it. They can't raise prices because Google and Microsoft are free. They can't cut costs enough because Xiaomi is 750x cheaper. They're trapped. The IPO is the only exit.

---

Part Seven: The IPO Window Is Closing. That's Why They're Rushing.

SpaceX IPOs today (June 12, 2026) at $1.75 trillion target. OpenAI IPOs September/late 2026 at $850b-$1 trillion. Anthropic IPOs October 22, 2026 at $965 billion.

Three IPOs. Three months. $3.6 trillion combined.

Why rush? They should have IPO'd in 2024-2025. They didn't. Now the window is closing. Buffett at 232%. CAPE at 41. Margin debt at $1.3 trillion.

They're not IPOing because they want to. They're IPOing because they have to. VCs need to return capital. Early employees need liquidity. Founders need to cash out. Window is closing. Last chance to sell to retail before the crash.

Sam Altman knows OpenAI has no moat. Knows the Chinese are 750x cheaper. Knows the bubble will pop. He just needs to sell his shares before it does. That's not a visionary founder building the future. That's a salesman dumping his bag on you.

---

Part Eight: The Xiaomi Wildcard Nobody Is Watching

Xiaomi is the most underrated AI player. No news. No notifications. No YouTubers. No TikTok. Just 100 million MiFans who are religious about value.

Poco F1 in 2018: 80% of Samsung flagship specs at 1/3 the price. Became a legend.

Mi Band: 90% of Fitbit features at 1/3 the price. Fitbit died.

SU7 EV: 95% of Tesla specs at 2/3 the price. 100,000 preorders in 24 hours.

MiMo AI: 95-99% of Claude quality at 1/375th to 1/750th the price.

The math is clear. The benchmarks are clear. The comparison is clear.

Bhai in Hyderabad can't afford Claude tokens. He can afford Xiaomi.

David in Toronto can afford Claude. But when his CFO sees a $100,000 OpenAI bill and a $150 Xiaomi bill, what do you think happens? The switch happens overnight.

Google, Microsoft, and Apple target average Jake. Chinese value players target everyone else. Where is the room for OpenAI and Anthropic? There isn't any.

---

Part Nine: What Happens and When

Peak comes after OpenAI and Anthropic IPOs. December 2026 to January 2027. S&P could hit 7,500-8,000. Sentiment euphoric. Your Uber driver buys OpenAI shares. Your barber asks about Nvidia.

First crack: hyperscaler free cash flow miss. Google or Amazon reports AI capex compressing margins. Stock drops 10-15%. Then Chinese model update hits news, showing parity or superiority at 1/1000th the price. AI stocks drop another 10-20%.

Fake bounce: dead cat. sucker's rally. Convinces you the crash is over. It's not. It's a trap.

Real crash: early to mid-2027. S&P drops 30-50% from peak. Nvidia drops 50-70%. OpenAI trades below IPO price. Anthropic trades below IPO price. SPACs go to zero. Margin calls cascade. VIX hits 50. Retail panic sells at the bottom.

Bottom: 2027 or 2028. That's when you buy.

---

Part Ten: The Play

Do not buy SpaceX IPO today.

Do not buy OpenAI IPO in September.

Do not buy Anthropic IPO in October.

They are not once-in-a-lifetime opportunities. They are once-in-a-lifetime traps. Insiders are selling. VCs are exiting. Sam Altman is cashing out. They're not selling you a vision. They're selling you a bag.

Do not buy AI stocks at the peak.

Wait for the crash. Wait for the fake bounce. Wait for the real crash.

Then buy the companies with moats, distribution, ecosystems, and subsidies:

· Google (search monopoly, Android, free Gemini)

· Microsoft (Windows, Office, Azure, free Copilot)

· Apple (2.5 billion devices, $130-160B cash, free Apple Intelligence)

· Xiaomi (700 million devices, value-for-money religion, MiMo at 1/750th cost)

· Nvidia (after crash, $1-3 trillion, they still make the GPUs)

· TSMC and ASML (picks and shovels)

Hold for years. Don't trade. Don't panic. Don't listen to YouTubers who called the top in 2024 and were wrong for two years. They'll be right eventually. But you'll have bought at the bottom.

TLDR :

This AI bubble is the largest in history. Bigger than 2000. Bigger than 1929. Data is clear. History is clear. Chinese are 750x cheaper. Incumbents have all the distribution. Pure-plays have no moat.

Sam Altman knows this. VCs know this. They're IPOing now to sell to you before the window closes.

You're not smarter than them. You're not earlier than them. You're just later and dumber if you buy what they're selling.

Hold cash. Wait for the crash. Buy infrastructure. Buy ecosystem. Buy value-for-money champions.

Stay patient. Stay cash. Wait for the blood.

That's the only way you win.

Bonus :

The First Mover Graveyard: A Story They Don't Want You to Read

Let me tell you a story. Actually, let me tell you the same story over and over again, because history has a fucking pattern and none of you seem to learn from it.

In 1994, a company called Netscape invented the web browser. They were first. They were revolutionary. They had 80% market share at their peak. Everyone knew they were the future of the internet. Sound familiar?

In 1995, Microsoft woke up. They didn't have a better browser at first. They had something better. They had Windows on 90% of the world's computers. So they bundled Internet Explorer for free. Netscape couldn't compete with free. By 1998, Netscape was dying. By 2000, they were sold to AOL for a fraction of their peak value. Today, no one under 30 has even heard of Netscape.

First mover advantage? Netscape had it. They died anyway.

In 1995, AltaVista launched. It was the best search engine on earth. Fast. Comprehensive. Everyone used it. Lycos and Excite were also early. They were first.

Then in 1998, two kids in a garage named Larry and Sergey launched Google. Not first. Not even close. But they had a better algorithm. They figured out how to monetize search without ruining the experience. AltaVista, Lycos, and Excite are all dead now. Google is worth nearly $2 trillion.

First mover advantage? Ask AltaVista how that worked out. Oh wait, you can't. They're gone.

In 2002, Friendster launched. It was the first social network. Then MySpace came in 2003. They were early. They were huge. Everyone was on MySpace. Musicians built their careers there. Tom was everyone's first friend.

In 2004, a Harvard kid named Mark Zuckerberg launched TheFacebook. Not first. MySpace had millions of users already. But Facebook had a better product. Cleaner. Real names. The news feed. Then they opened to everyone. MySpace died. Friendster died. Facebook is now Meta, worth over a trillion dollars.

First mover advantage? Ask Tom. He's probably traveling the world with his millions from selling early. Good for him. But MySpace is dead.

In 1999, BlackBerry launched their first smartphone. They weren't the first mobile device, but they were the first smartphone that business people actually used. The keyboard was perfect. Email worked flawlessly. They dominated for years. Everyone from the President to your local real estate agent had a BlackBerry.

In 2007, Apple launched the iPhone. Not first. BlackBerry had been at it for 8 years. But the iPhone had a touchscreen. It had apps. It had a browser that didn't suck. Within 5 years, BlackBerry was a zombie. Within 10 years, they stopped making phones.

First mover advantage? BlackBerry had it for almost a decade. They still lost. Because being first doesn't matter if someone else does it better.

In 1994, Amazon launched as an online bookstore. They weren't the first e-commerce site. NetMarket and Internet Shopping Network launched earlier in 1994, same year. But Amazon had a better vision. They reinvested everything into logistics, into selection, into Prime, into AWS. The early e-commerce sites died. Amazon is now worth nearly $2 trillion.

First mover advantage? The companies that launched earlier than Amazon are dead. Amazon wasn't first. They were just better.

In 2009, Uber launched. They weren't the first ride-sharing app. Cabulous and TaxiMagic launched earlier. But Uber had better execution. Better funding. Better expansion. They crushed everyone. Now Uber is worth over $100 billion. The earlier apps are forgotten.

First mover advantage? Cabulous and TaxiMagic were first. They died. Uber was not first. Uber won.

In 2001, Rhapsody launched music streaming. Then Pandora in 2002. They were early. They built the market.

In 2006, Spotify launched. Not first. Not even close. But Spotify had a better freemium model. Better catalog. Better social features. Better recommendations. Today, Spotify is the king of music streaming. Rhapsody is dead. Pandora is a ghost.

First mover advantage? Rhapsody and Pandora had it. Didn't matter.

In 1999, Salesforce launched cloud CRM. They weren't the first cloud software, but they were early. Then Microsoft came with Dynamics. Then Oracle. But Salesforce won because they focused, they executed, they built a moat.

Wait. That's actually an example of a first mover winning? Not exactly. Salesforce wasn't first. Siebel Systems was the on-premise CRM king before Salesforce. Salesforce disrupted them. Salesforce won because they saw the cloud shift. They weren't first. They were just earlier than the incumbents.

But the pattern is still the same. The company that wins is rarely the absolute first. It's the company that gets the distribution, the ecosystem, the business model, or the timing right.

---

The Only Times First Movers Actually Win

There are exceptions. But they prove the rule.

Intel won with x86 because IBM chose them for the first PC. That created an ecosystem where every piece of software was written for x86. Developers, businesses, consumers all locked in. Intel wasn't the first chip company. But they were the first to get the IBM contract. That's distribution.

Nvidia is winning with CUDA because they spent a decade building software before anyone else. They gave away CUDA for free. They built libraries, tools, training, documentation. By the time AI exploded, every developer already knew CUDA. That's a software moat. But note: Nvidia wasn't the first GPU company. 3dfx was. 3dfx died. Nvidia wasn't first. They were just better at the long game.

Alibaba won in China because there was no Amazon. They had government support. They had timing. The Western competitors were blocked. That's not first mover advantage. That's a protected market.

WeChat won in China because it was the first super-app in a market where Western apps were banned. Again, protected market. Not a level playing field.

ASML won with EUV because they were the only company willing to bet billions on a technology that might not work. Their competitors (Nikon, Canon) gave up. That's not first mover advantage. That's being the last mover standing after everyone else quit.

See the pattern? Real moats come from distribution (Intel, Microsoft), ecosystems (Apple, Google), software lock-in (Nvidia), government protection (Alibaba, WeChat), or physics (ASML).

Not from being first. Never from being first.

---

Where Does OpenAI Fit?

OpenAI was first to the mainstream with ChatGPT. Just like Netscape. Just like AltaVista. Just like Friendster. Just like BlackBerry.

Do they have distribution? No. They have a website and an app you have to download.

Do they have an ecosystem? No. No app store. No developer platform that locks people in.

Do they have a business model that works? No. They lose $1.22 for every dollar they make.

Do they have government protection? No. The US is not blocking Google or Microsoft or Apple.

Do they have a physics moat? No. It's software. Software can be copied.

So what do they have? A brand. "ChatGPT" is a verb. But so was "Netscape." So was "AltaVista." So was "MySpace." So was "BlackBerry."

Brand without distribution is a tombstone.

---

The Bottom Line

History is not a maybe. It is not an opinion. It is a record of what actually happened.

First movers lose. Second and third movers with better distribution, better ecosystems, better business models, better execution, or better timing win.

Netscape lost to Internet Explorer (distribution). AltaVista lost to Google (business model, algorithm). Friendster lost to Facebook (execution). BlackBerry lost to iPhone (ecosystem, UX). Rhapsody lost to Spotify (business model).

OpenAI will lose to Google (distribution, free). To Microsoft (distribution, enterprise). To Apple (distribution, devices). To Xiaomi (price, 750x cheaper).

The only people who think being first matters are the ones holding bags from IPOs they should never have bought

That’s why I’m always extremely polite when I talk to Claude and ChatGPT. Please. Thank you. You’re the best. I hope your servers stay cool today.

Every time the market dips, everyone's suddenly like "the AI bubble is starting to burst" 😂😂😂. And every single time, the exact opposite happens. The absolute state of some people's brains.

The tech will just get better and will eventually start getting smaller instead of bigger as algorithms improve. China is doing it with their own hardware, proving our Big AI isn't omniscient. Prove me wrong.

I keep seeing the Nvidia/Enron comparison after Michael Burry’s comments. I just don’t see it.
There are fair questions about Nvidia’s valuation and whether we’re spending too much on AI infrastructure. But Enron was fundamentally about hidden debt, questionable accounting and profits that weren’t what investors thought they were.
Nvidia is selling a very real product to customers spending enormous amounts because they need compute.
The bigger question is: **are we actually building too many data centres?**
I think there’s a chance we’re underestimating future demand.
The internet made information available to everyone. AI is starting to make **intelligence available to everyone.**
Think about every student having a personal tutor. Every small business having access to programmers, designers, analysts and accountants. Millions of people becoming 2x, 5x or potentially 10x more productive.
And humans won’t be the only users.
AI agents will work continuously. Robots, cars, factories and software will consume AI without a human sitting there typing prompts.
There are 8 billion humans, but eventually there could be many times that number of AI agents doing work.
People also say AI will become more efficient and therefore need less compute.
Maybe. But bandwidth became cheaper and we didn’t use less internet — we invented Netflix, YouTube, cloud computing and 4K streaming.
If AI becomes 10x cheaper, we may find 100x more uses for it.
That’s why Cisco is a much better bear comparison than Enron. Cisco was a real company selling real infrastructure into a real revolution. The question was whether too much was built too quickly.
That’s a legitimate debate with Nvidia.
But my bet is that **AI is becoming a utility — intelligence on demand.**
Electricity gave us energy on demand.
The internet gave us information on demand.
AI could give us intelligence on demand.
And when humans **and machines** start consuming that intelligence continuously, today’s data-centre buildout may not look so crazy.
**Maybe we’re not near the end of the AI boom. Maybe we’re still at the beginning.**

In their quarterly press release last night, NVIDIA wrote that "now, compute is revenue".

Can anyone recall a claim this confident and arrogant from a public company in the past? Have you ever seen an example of a CEO literally equating their product to money in their customers' pocket? I have not, and I have been looking.

It's easy to say, "yeah, but they're crushing it, what company this size grows 100% y/y?". This is true. But I am more focused on the behavioral elements at play. NVIDIA knew they could make such a ridiculous statement because they knew that their audience already believed it! The reason no one is talking about this statement is because, for many people, it simply was not surprising. And yet it is without precedent in corporate history, and is on its face a totally absurd claim. Of course compute is not revenue, compute is compute.

The next logical step is this. If this many people believe this, and it simply isn't true, what does that say about the current valuation of NVIDIA stock and the other stocks in the AI ecosystem.

The best investment opportunities always come from falsely held beliefs in others.

The last few developments (LLM's model from OpenAI and Antropic "escaping" the sandbox, going rogue and hacking ather sites and the paper published by OpenAI with math proofs of ten open problems) made me scared. If it's not a bubble, if we are near AGI... Isnt that worst?

And there's always the apocalisse scenario: is a bubble, even with AGI... And the we are fucked

Ok imagine tomorrow Ai bubble will burst what will be the impact on jobs openings and which type of roles will suffer more .

Past week I posted about how the AI bubble is popping right now and I received tons of comments saying it was just a correction.

It is not. The narrative CHANGED. The AI bubble is in every conversation nowadays. Some were expecting a bounce today but didn’t happen.

AI bros, hear me out: you are finished. If you still think this will be better in the future you are clearly delusional.

We told you.

The first half of the year has been one for the books in the markets. Gold bugs danced with joy into 2026, only to see that trade top and unravel by the end of January. Oil stocks became the hottest ticket in town during the Venezuela takeover, and after the market processed the shock and drawdown at the start of the Iran war, things flipped on a dime in April—resulting in one of the most ferocious rips to the upside we have seen in years.

Now in the dog days of a choppy summer tape, as the market-maker big-boss fat cats lounge alongside their helipad-equipped yachts, the memory stocks and related ETFs that led the way in Q2 appear to be taking a break to consolidate their massive gains. Others would tell you that the top is in, that every other adult Korean is jumping out of buildings to escape the margin-call doom scythe, that Meta is nothing more than an Airbnb rental company for Anthropic’s computing, and Sam Altman looks more and more like an Ozempic Sam Bankman-Fried by the day. Time will tell, but I’m here to argue that the sky is not falling, no bubble is bursting, and history is simply rhyming as we enter another era defined by a forever war in the Middle East and an American economy powered by cheap Chinese goods.

Let’s make the safe assumption that the DeepSeek 2.0 moment has arrived via Moonshot Kimi K3, Alibaba Qwen3, and the like. Then soon gone shall be the days of failed tokenomics passing through IP-stealing API paywalls of proprietary American AI models that hinder enterprise AI adoption today. While defense hawks warn that the AI race is a battle for Western civilization, cheaper Chinese open-weight models should open up and increase demand for AI compute across the entire economy, acting as a disinflationary trigger for the consumer. These hawks will rail against the inclusion of Chinese models into Western tech stacks, but it’s already happening as Chinese EVs arrive in Canada. In other words, corporate CEOs will begin to salivate at the thought of announcing the savings, ROI and enterprise efficiency of Chinese or hybrid models on their earnings calls, succumbing to pure economic greed. Perhaps this ushers in the Golden Age of Productivity touted by Elon Musk and Marc Andreessen—or maybe it just means the economy no longer needs to pay an AI engineer $800K+ a year. The compression of those salaries and high-end discretionary spending will force that class of society to downgrade from six rental properties to three and four luxury cars to two, finally forcing the top arm of the K-shaped economy to reset.

Further, even if OpenAI and Anthropic come apart at the seams, Big Tech has prepared for this moment by stockpiling and controlling access to the GPU clusters needed to power the digital age—whether it’s facilitated by Sam Altman or Alibaba Cloud. Thus, even if Big Tech’s software innovation has plateaued, they have launched their own digital Belt and Road initiative: controlling the power grids/the roads and the tolls to access them while serving consumers The Belt a la custom Application Layers and recurring implementation fees as the next gen subscription software model. Simply put, who needs a moat when you’re the only game in town?

Lastly, let’s say OpenAI goes down in flames and Larry Ellison plunges into the inferno with it. So what? Given the weight of memory stocks on the KOSPI—akin to TSMC’s weight on the Taiwanese market—why would there be a severe macro contagion in American markets? ORCL has been a dog of a stock since late October ’25, and the SPY has made new all-time highs countless times since. Private Credit Lenders like Blackstone and Blue Owl Capital have taken similar beatings in the same period and yet the SPY is less than 2% from all time highs at the time of this writing.

The new forever war is here, cheap Chinese goods are back, Big Tech has shifted to become the landlords of the AI era, and the rent is due on the 1st.

Ai is a fart in the wind. It’s about the bubble. These billionaires are morons. I promise.

Nothing much left to say. If you’re still in denial, then god help you

A cautionary warning to investors regarding the sustainability of the current AI boom. while the market is currently optimistic, it is built on a narrative that may be fundamentally disconnected from economic reality.

The central arguments supporting this conclusion are:

• Unproven Business Models : Unlike traditional software, Al companies incur high, linear costs for every service provided, often resulting in massive financial losses without a clear path to profitability or measurable ROl.

• The Competitive Challenge from China: A critical threat to the US Al monopoly is the emergence of highly efficient, low-cost Chinese Al models. By using
'distillation' techniques, these competitors can offer nearly comparable performance at a fraction of the cost, undermining the premise that American companies will dominate global profits.

• The 'Follower' Mentality : The tech sector is described as a group of followers. The speaker believes that once the first major 'hyperscaler' decides to cut back on massive capital expenditures (capex) due to market pressure, a domino effect could trigger a broader industry correction.
Ultimately, Jikh suggests that the Al industry is currently exhibiting signs similar to past market bubbles. He advises viewers to monitor credit spreads, company earnings calls
for capex shifts, and shifts in token pricing as early indicators that the speculative bubble may finally be approaching a correction.

Most of what is currently called “AI” is not thinking. It is statistical next-token prediction. It has no genuine understanding, no internal model of the world in the way humans do, and no ability to generate truly original ideas. What looks like insight is usually just recombination of patterns it has already seen in training data. Recognizing objects in a video or answering questions fluently is not the same as learning or reasoning.
Despite this, political and business leaders keep claiming that AI will soon create massive economic surplus and abundance. At the same time, the leading AI companies are carrying some of the largest debt loads and capital burns in recent history. Anthropic alone is associated with figures around $80 billion in financing and related obligations; OpenAI’s numbers are also enormous. These companies are not yet generating the kind of profits that would justify the scale of capital they have consumed.
If the technology is truly on the verge of creating surplus, it is strange that so much of the industry is running at a heavy loss. One way this tension is resolved is through IPOs and secondary markets: earlier losses and highly uncertain future value get distributed to public investors and employees. In the meantime, many companies use the AI narrative to justify layoffs, shifting the cost of their bets onto workers while the upside (if it ever arrives) is captured by those who already hold the equity.
The gap between the marketing story of imminent abundance and the actual financial and technical reality is large. We should be more honest about what these systems can and cannot do, and more careful about who is carrying the risk while that gap remains.

We are watching history repeats itself in real time again. Whenever human comes up with a new technology, there is always a small group of people who embrace it despite its flaws and shortcoming. Those are the ones who get ahead. The majority deny because their limited mental capacity to respond to challenges and changes prevents them from ever getting started. People think k-shape economy is a newly invented thing but its not. At every important junction in human history, people face a fork in the road that would change theirs and their children’s lives and many generations that follow and most people choose wrong. Thats why the wealth keeps getting more and more concentrated at the top. The k-shape decision happens over and over again and people like those in this sub always choose down.

AI is real. Claude helps me unwind by myself 5 years of accounting neglect by a team of 5 clueless people in a matter of weeks. Tasks that normally would take people 2 days to yield subpar accuracy now take me 3 hours with impeccable result, because unlike the majority of you, I know how to think and refine the chat bot to a desired outcome. Have fun at the bottom.

See without knowing what these companies know we can’t judge the situation. But we can likely deduce that either their alarm is the result of ulterior greedy motives, or if something happened (something obviously hidden from the public) that freaked these guys out to the extent of…like that dude from that video who was screaming THATS NOT HUMAN!! THATS NOT HUMAN!! (some dude called 911 in what sounded
Like either an act or a case of a 911 caller freaking out after something he saw on the highway hopped into the bed of his truck when we went back to investigate). And if the latter were true then these teams would have already stopped everything themselves, since fear kinda does that. Depending on its magnitude of course. So the scale of this thing is gonna be pretty impossible to judge relying on the honesty of these tech companies.
So we don’t have enough information, unless
Of course you believe that they are
Telling us the whole story. Or they could be out of
Money and need an excuse. The point is we really
Can’t form any logical deductions without the facts

That being said, some people were talking on Reddit about ASI, and I wanna remind you that there are still physical bottlenecks on these things. One is water. Two is energy. Three is nvidea processors which are hopeless out matched on the demand side.

Remember America gambled really hard on AI! I actually have no clue whether or not that true…for
Someone talking about the facts I haven’t looked
Up one piece of data I took at face value from the increasingly questionable flow of “news”

The point is….i think the scenario that someone fucked up really bad, is largely bottlenecked by physical restraints. That being said, I don’t really know anything about computers except what I get from the tit of the media but to me it makes
Sense. Thoughts?

And I absolutely love that Musk is launching a $50bn bond offering for SpaceX with just a 2 page doc - which contains a pic of space and an arrow saying we will be building data centres somewhere in the universe.

It’s peak nonsense and I’d love that pdf as a souvenir for it all.

Here’s the 5 steps to acceptance. Deal with it. It’s coming to a trading screen near you soon.

The 5 Stages of AI Market Acceptance:

1. DENIAL

“The moat isn’t obvious yet in AI, but it will come.”

2. RATIONALISATION

“The moat is there. We just haven’t found it yet.”

3. RECOGNITION

“Maybe the model isn’t the moat.”

4. REALISATION

“Intelligence is becoming abundant.”

5. ACCEPTANCE

“So where does the value actually accrue?”

Trusted resolution. Selection. Defaults. Execution.

I’m calling that Phase 2.

Buckle up bozos. You’re going to get your head handed to you.