Say Farewell to the AI Bubble, and Get Ready for the Crash

I remain convinced the whole hype was a way to overfire after the big overhire.

But who's to say humans are any different than simple databases with probability and statistics firing neurons??

/s

No they won't. They won't struggle to explain anything because in US business culture, nobody ever actually takes blame except underlings. Nobody ever even asks them to explain themselves. Even in public companies it seems like questions from shareholders that actually get asked in quarterly calls are vague humble brags. "What are we going to do about the problem of winning so hard" while they had record layoffs the previous quarter.

Those talking heads haven't had to mea culpa for : Hype about Hadoop, hype about blockchain, hype about no code, hype about the previous AI bubble, hype about "agile", hype about whatever JS script is popular this week, etc.

this is just wrong

you could say "it's just matrix multiplication"; but then quantum mechanics (and thus chemistry, biology, and everything on top of that) is just linear algebra

The internet didn't go away after the dotcom crash in early 2k, so the AI *IF* such crash happens.

There're a lot of business discovering its benefits now, companies will continue building things over it.

Initially politicians were responsive. In Feb. 2024 he sought trillions of investment to ramp up "AI" [1]. Then he got the White House announcement with Trump and Softbank for the $500 billion Stargate deal. The project has flopped, only one data center will be built.

So I assume he thought hype would work again, but people are beginning to scrutinize the real capabilities of "AI".

[1] https://www.wsj.com/tech/ai/sam-altman-seeks-trillions-of-do...

I'm starting to think he's playing the long game. To make OpenAI what Amazon and Google were in the dot com bubble. The last people standing.

And he's not the only one, a handful of companies are well aware that we're nearing the peak of a hype cycle and making sure they can survive the burst.

I was just in the Louisiana public service commission meeting where Entergy told the regulators that Meta Platforms was worth 2 trillion and they got some opinion from a New York law firm that their word was good so YOLO. Passed 4-1. The exact words were “Meta Platforms is worth more than the five biggest banks combined” (implying no point in asking a bank for a loan guarantee or backstop)

There was a lot of business value during the dotcom boom and we still had a crash. The question is how many AI companies have strong fundamentals and will survive, vs the ones that have weak fundamentals and will die if/when the investment money dries up.

I also consume all the heavily sibsidized LLM tokens I can find a use for. Great deal for us, the people who funded it?

Not so fun.

95 per cent of organisations are getting zero return from AI according to MIT - https://news.ycombinator.com/item?id=44956648 - August 2025

State of AI in Business 2025 [pdf] - https://news.ycombinator.com/item?id=44941374 - August 2025

https://web.archive.org/web/20250818145714/https://nanda.med...

> Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return. The outcomes are so starkly divided across both buyers (enterprises, mid-market, SMBs) and builders (startups, vendors, consultancies) that we call it the GenAI Divide. Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact. This divide does not seem to be driven by model quality or regulation, but seems to be determined by approach.

I used the internet every day in 2000. Bubbles happen with useful technologies not because we decide they aren't useful, but because we were over-sold on what they could do before they could do it.

A lot of AI investment right now is hinged on promises of "AGI" that are failing to materialize, and models themselves are seeing diminishing returns as we throw more hardware at them.

Crashes also happen when there is a huge mismatch between price and value.

I use my house all day and I'm sure I'm not the only one.

that didn't stop the housing bubble in the 2000s.

likewise, if I argue that Dutch "Tulip mania" [0] was a bubble, "but tulips are pretty" is not an effective counter-argument. tulips being pretty was a necessary precondition for the bubble to form.

the existence of a foo bubble does not mean that foo has zero value - it means that the real-world usefulness of foo has become untethered from market perceptions of its monetary value.

0: https://en.wikipedia.org/wiki/Tulip_mania

I made this comment earlier, and its just easier to copy it:

>Theres 2 AI conversations on HN occurring simultaneously.

> Convo A: Is AI actually reasoning? does it have a world model? etc..

> Convo B: Is it good enough right now? (for X, Y, or Z workflow)

The internet reshaped the entire global economy, yet the dot com crash occurred all the same.

Convo A leads to questioning if the insane money being poured into AI make sense. The fact that many people are finding utility, doesn't preclude things from being over valued and over hyped.

Two things can be true simultaneously:

a) AI is an extremely useful productivity tool to accomplish tasks that other programming paradigms can't do.

b) Investment in AI is disproportionate to the impact of (a), leading to a low probability of sufficient ROI.

There is definitely value but not sure if it is as much as the AI bosses are promising. I don’t know if it will crash or not but they are definitely overselling it. GPT-4o to 5 is so incremental compared to 3.5 and 4.

> Crashes come when there was no real business value.

You fall into all or nothing logic. That's thinking failure.

If real business value is 10% of the price, there will be massive crash and years of slow advance.

Dot-com bust was like that. Internet clearly had value, but not as much and not as quickly as people thought.

The issue isn't that AI has no value but that the amount of money invested in it is out of proportion to the value it's going to generate within a reasonable time frame. Useful new technologies are invented all the time. But not many of them will yield a return on a trillion dollar investment.

My take is the reckoning will come for the billion businesses that offer B2B AI solutions that don't offer any meaningful value. "Analyze customer intent and improve conversion with XYZ AI!" The tools of the AI revolution will continue to exist though development (read money) will presumably slow as businesses recalibrate and stop paying for the silver bullet solutions that they discovered don't work. Then the snake oil business people who built businesses around LLMs will move onto whatever BlockChain 2 Electric Boogaloo looks like.

Crashes, rather, must come when there is an enormous, industry-wide mismatch between perceived value (e.g. assessed in terms of expected return on investment) and actual value in terms of real return on investment within the expected period.

Evidence is emerging that the former could be twenty times the latter, or more.

The value you perceive has been much, much more expensive than investors would like, I suspect.

There’s a $5 bill taped to every prompt you do. It’s unlikely you’d be using it all day if you were paying by the drink.

> Crashes come when there was no real business value.

Indeed. That's why we don't have trains or the internet anymore; once they had their big crashes we knew there was no business value, so they went away.

... I mean, what? You generally can't get a big bubble without _some_ business value, so bursting bubbles almost always have _something_ behind them (the crypto one may be the exception).

Internet traffic kept growing throughout the dotcom bubble. That valuations got ahead of themselves didn't mean that there wasn't something real driving the hype.

Even if AI valuations have a sharp correction, there will still be a great need—and demand—for compute.

tap tap tap

I've never met a "thought leader" whose opinion was worth anything.

Have bubbles ever been successfully called by thought leaders?

Is Sam Altman a thought leader?

Never quite realized how much I disliked the term "Thought Leader" until I read it 5x in the comments responses of this thread.

But people being just a "thought leader in the space" is exactly the reason there's a bubble.

Bubbles are a lot easier to visualise from the outside.

It's just another anecdote, but the "vibes" feel like they're shifting.

The employment numbers, the inflation numbers, government austerity, the gpt-5 disappointment... the valuations are all more like meme stocks and not based on reality.

If enough articles about the crash start appearing, and enough people believe the crash is coming, the congratulations: the crash will occur.

> What a bad article. I mean how biased can you be, to put the first big quote from someone who wrote a book called "The AI con".

It's an op-ed. It's supposed to be biased.

This is an Opinion piece, not a news article. The distinction between the two seems to be lost on most people nowadays.

One way I leverage opinion pieces for things with which I disagree, is to treat it as a sort of "devil's advocate". What argument are they making? Is that really the strongest one they have? Does my understanding of that domain effectively counter those arguments? etc.

In this case, the main argumentation is on how ChatGPT is not the miraculous genie it was hyped up to be. That's a fair statement, but to extrapolate that into "AI bubble is crashing now" is overlooking a host of other facts about its usefulness. Yes we'll eventually hit the through of disillusionment but I don't think we're there yet.

> gpt5 has always been about making a "collection of models" work together and not about model++.

That is revisionist history. Look at Altman's hype statements in the weeks and months leading up to gpt5, some of which were quoted in the article. He never proposed gpt5 as what you're saying and indeed he claimed a massive leap in model performance.

> gpt5 has always been about making a "collection of models" work together and not about model++.

No, it wasn’t. Have you read and listened to Altman’s hype around GPT-5 from a year ago? They changed the narration after the 4.1 flop, which they thought would be GPT-5, and it seems some people fell for it.

> Capabilities ~90-110% of their top tier old models at 4-6x lower price

Maybe they finally implemented the DeepSeek paper.

> This was announced what, a year ago?

Source? Others are calling out this as being incorrect, so a source would help people evaluate this claim. Personally I'm much more likely to believe that AI companies are moving the goalposts rather than making significant leaps forward.

I have a feeling if someone wrote an article about how great GPT-5 is and the first big quote was from Sam Altman, you'd say it's a cool article.

It's only "bias" when you don't like it.

Media orgs (well journalists really) are especially hostile towards AI and it's easy to see understand why.

Meanwhile Claude is helping me build a robot and is also writing the code that runs its subsystems but okay. Sure, I could do it all myself(maybe?) but not nearly as quickly or in the interstitial moments of life.

Interesting hypothesis.

One could argue the same was true of blockchain until AI came along.

> large language models work comparatively well with (programming) languages

what else would they be good at

Yeah Altman says "I think we totally screwed up some things on the rollout" https://fortune.com/2025/08/18/sam-altman-openai-chatgpt5-la...

also

>ChatGPT is already the fifth biggest website in the world, according to Altman, and he plans for it to leapfrog Instagram and Facebook to become the third, though he acknowledged: “For ChatGPT to be bigger than Google, that’s really hard.”

>“We have better models, and we just can’t offer them, because we don’t have the capacity,” he said. GPUs remain in short supply, limiting the company’s ability to scale.

So Altman wants to keep building. Whether investors will pay up for that remains to be seen I guess.