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How the AI Bubble Bursts

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Re: How the AI Bubble Bursts

#371

Post by aurareturn »

the_gipsy wrote: post #358
aurareturn wrote: post #92

This is an awful article. I don't know how it reached #1 on HN. Bottom line is that H100 prices are near 3 year highs, A100s are still profitable to run, B200 prices are increasing, no one has enough compute. Google, OpenAI, Anthropic, Meta, AWS, Azure are all compute constrained. Every single one of them said so publicly. Neo clouds are telling customers they're all sold out now and you even have to book compute in…

> but Anthropic is kicking butt in AI that's not what the article said: > They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them

Yes, that's what he said.

He said AI is going to bust because OpenAI needs to put ads on free tier. Then he said Anthropic is doing great with enterprise customers.

So which is it? Is AI going to burst because OpenAI needs to put ads on ChatGPT? Or is AI not going to burst because Anthropic is doing great in enterprise?

The logic has glaring flaws.

Re: How the AI Bubble Bursts

#372

Post by nunez »

aurareturn wrote: post #92

This is an awful article. I don't know how it reached #1 on HN. Bottom line is that H100 prices are near 3 year highs, A100s are still profitable to run, B200 prices are increasing, no one has enough compute. Google, OpenAI, Anthropic, Meta, AWS, Azure are all compute constrained. Every single one of them said so publicly. Neo clouds are telling customers they're all sold out now and you even have to book compute in…

> I think AI agents could completely replace Microsoft Office

How? What do you think lawyers/government will use to write briefs?

Re: How the AI Bubble Bursts

#373

Post by user34283 »

pydry wrote: post #281
adventured wrote: post #234

Earlier quoted context omitted.

LLMs haven't remotely begun to be integrated into the lives of the typical person. Not even close. The typical person is using LLMs not at all as it pertains to their daily life tasks. They're using them almost entirely for limited discussion matters (eg having a discussion with GPT about a medical issue, or a work related matter). This is the first or second inning in the LLM rollout. It'll take 15-20 more years for…

>The typical person is using LLMs not at all as it pertains to their daily life tasks. This doesnt track at all with my experience. Everybody is using it everywhere. Moreover people are using them for daily life tasks even when it is not an appropriate use of LLMs - e.g. getting medical advice as you referred to or writing emails which are clearly pissing off their coworkers. In this respect I see it as akin to radiu…

In my experience people vastly overestimate the competence of doctors. Getting medical advice from LLMs could be life saving.

Personally I experienced this when a specialized doctor believed a drug interaction to be the opposite, thinking A hinders the absorption of B, when actually it hinders the clearance, tripling concentration of B.

Without AI, I would have been clueless about this and could not have spotted the mistake. I don't know if it would truly have been critical, but it did shake my confidence in doctors.

Re: How the AI Bubble Bursts

#374

Post by aurareturn »

arctic-true wrote: post #338
aurareturn wrote: post #139

Earlier quoted context omitted.

I don't have any evidence. You'll have to believe what Anthropic and OpenAI CEOs say publicly. However, it seems to make a lot of sense. Anthropic literally added $6b ARR in February 2026 alone. I doubt training costs go up that fast.

But this is exactly the problem - we have to take it on faith that inference is profitable because nobody actually knows. It’s hard to even define what that would mean, and while I am suspicious of claims that frontier lab CEOs are just out-and-out liars or bad people, defining and calculating the real cost of inference would be time- and labor-intensive in its own right and there is no strong incentive to do it othe…

A lot of people know. A lot of insiders have been saying tokens are profitable. Is there a conspiracy theory for everyone to lie? Including OpenAI, Anthropic CEOs, employees, Cursor management, inference providers of Chinese models?

Re: How the AI Bubble Bursts

#375

Post by mNovak »

joshstrange wrote: post #53

> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…

This feels similar to when Deepseek first debuted with claims of ultra-low cost training, and all the pundits exclaimed that Nvidia was finished, the bubble had burst, etc.

Re: How the AI Bubble Bursts

#376

Post by [deleted] »

flir wrote: post #337
raincole wrote: post #286

Earlier quoted context omitted.

It is quite hard to imagine how the demand is saturated now. I think any company that uses a sliver of AI will happily increase their token consumption 100x if it's free.

Are you assuming a brute force "burn tokens until it passes the tests" model, or is there a really sweet approach on the horizon that is impractical at current token costs? I'm asking 'cos while I'm philosophically opposed to the first option, but I'd love to hear about anything that resembles the second.

[deleted]

Re: How the AI Bubble Bursts

#377

Post by fatata123 »

Marha01 wrote: post #336
pydry wrote: post #153

Earlier quoted context omitted.

Jevons paradox only applies if demand hasnt already been saturated. The fact that public LLM usage is leveling off at a price of $0 and Jensen "we make the shovels in this gold rush" Huang is rather desperately claiming that you need to spend $250k/year in tokens to be taken seriously suggests that demand saturation may not be that far off. Whether Jevons' Paradox applies to software engineers I think is another open…

Demand for top models is definitely not saturated, at least when it comes to programming. If I could afford to use 5x more Claude Opus 4.6 tokens, I would!

[dead]

Re: How the AI Bubble Bursts

#378

Post by itintheory »

sergiotapia wrote: post #363
drakythe wrote: post #160

Earlier quoted context omitted.

Is there a source that says commercial RAM prices are dropping? I was recently told (without a source, so I am not sure if it is true or not) that OpenAI never even bought any of the RAM they signed deals on last year, and that those deals were just letters of intent. So if prices are coming down I wouldn't be shocked but the economy is pretty well vibe coded these days so who even knows.

here you go: https://x.com/wccftech/status/2037921057097892018 Ram prices are dropping

Every response to the original post calls it out as being factually incorrect...

Re: How the AI Bubble Bursts

#379

Post by hajile »

Marha01 wrote: post #336
pydry wrote: post #153

Earlier quoted context omitted.

Jevons paradox only applies if demand hasnt already been saturated. The fact that public LLM usage is leveling off at a price of $0 and Jensen "we make the shovels in this gold rush" Huang is rather desperately claiming that you need to spend $250k/year in tokens to be taken seriously suggests that demand saturation may not be that far off. Whether Jevons' Paradox applies to software engineers I think is another open…

Demand for top models is definitely not saturated, at least when it comes to programming. If I could afford to use 5x more Claude Opus 4.6 tokens, I would!

Demand is relative. How many Claude tokens would you buy if they had a 10x price hike?

The market has achieved it's current saturation level with loss-leader prices that remind me of the Chinese bike share bubble[0]. Once those prices go up to break even levels (let alone profitable levels), the number of people who can afford to pay will go down dramatically (and that's not even accounting for the bubble pop further constricting people's finances).

[0] https://www.youtube.com/watch?v=FQrEDq8KPiU

Re: How the AI Bubble Bursts

#380

Post by EthanHeilman »

woadwarrior01 wrote: post #125
amelius wrote: post #97

Earlier quoted context omitted.

> Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. I think it is determined: https://en.wikipedia.org/wiki/Jevons_paradox

Yeah, even if one efficiency trick lands, people will end up spending the saved budget right back on bigger models, and/or more "thinking" tokens.

Not if the bigger models have diminishing returns. Lets say you figure out a way to reduce RAM requirements 100X, but 2x increasing RAM usage by 2x only gets you a 1% increase in effectiveness and 3x does not get you any noticeable increase over 2x at all. Sure you can reduce the price per token, but you might have already saturated the market. Even if you haven't saturated the market, your hardware based moat just got smaller and this is going to reduce your margins even more.

Just noticed that pydry made a similar point: https://news.ycombinator.com/item?id=47574216

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