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How the AI Bubble Bursts

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Re: How the AI Bubble Bursts

#481

Post by zozbot234 »

pydry wrote: post #153
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

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…

> The fact that public LLM usage is leveling off at a price of $0

Tne price is very much not $0, even 'free' models have usage capacity limits that equate to a shadow-price.

Re: How the AI Bubble Bursts

#482

Post by niam »

fragmede wrote: post #479
niam wrote: post #453

Earlier quoted context omitted.

I don't discount this as a possibility but my impression is that the OpenAI brand isn't very sticky. Internet Explorer being pre-installed on Windows devices didn't prevent it from being demolished by newcomer Chrome throughout the 2010s. Now we're looking at a product that's even less integrated, and whose value is exposed through universal interfaces (human language, images, etc.). If OpenAI succeeds, I imagine tha…

For people that use ChatGPT the same way you do, yeah it's not. For people in the throes of AI psychosis who've named their ChatGPT and have a deep relationship with it, switching to a newer model from OpenAI is an issue, nevermind switching to a different model from a different company.

I considered that but I don't see it being very impactful. It presumes a user who cares enough about "their" ChatGPT that they can't move from a particular model provider, but simultaneously does not care enough that model providers themselves have a financial motivation to shoo users onto their newer and more efficient models.

The transition from GPT4 to GPT5 was not well recieved among this crowd -- nevermind that I think this crowd is pretty small (comparatively) to begin with. I just don't imagine you can build a business on that sliver of a sliver, much less one that justifies OpenAI's spending.

Re: How the AI Bubble Bursts

#483

Post by reverius42 »

fcarraldo wrote: post #196
SirensOfTitan wrote: post #56

Earlier quoted context omitted.

This is a classic HN mistaking the map for the territory. R&D and capex absolutely figure into de-facto profitability and sustainability for AI labs, despite their separate treatment in accounting. > well most of us here on HN have benefited from decades of overinflated engineering salaries being paid by often companies that were not profitable and not only unprofitable This is a really concerning perspective: people…

> Software is or was one of the few remaining arenas wherein a person can find a consistently Software salary inflation and expansion has made this the case. Tech’s accessibility to the educated has accelerated gentrification massively, rising up prices on rent and food. While the statement is correct, tech’s contribution to income inequality is part of the issue. If you’ve lived in Austin or Chicago (especially Aust…

I don't think there are enough well-paid tech workers to affect things like the (national) market for food. Local rent markets are at least partly explained by this; I agree that the $3M houses near Palo Alto, CA are because of Big Tech salaries, but not the price of ground beef.

Re: How the AI Bubble Bursts

#484

Post by reverius42 »

keybored wrote: post #211
guzfip wrote: post #191

Earlier quoted context omitted.

> As long as they are paid well compared to other workers, it’s fine. Well I’m sure they’ll be thrilled to know they can collect $100 a week more in unemployment benefits than their neighbor.

I wasn’t alluding to them resigning or whatever this comment is referring to.

I don't think you get to collect any unemployment if you resign.

Re: How the AI Bubble Bursts

#485

Post by mvdtnz »

> And independent of whether Microsoft makes money or not in their OpenAI endeavor, it kills the story: they were betting the whole growth story on AI, and if that doesn’t work out, then what’s left to justify a high stock price?

Microsoft's stock price today is the same as it was in late 2021 before anyone cared about AI. What would happen? Nothing. I don't think it's a significant revenue driver today. Microsoft, like everyone else, is speculating that AI will drive profits in the future. If it all fell apart there will certainly be losers but I don't see why it would bring down Microsoft.

Re: How the AI Bubble Bursts

#487

Post by pydry »

SpicyLemonZest wrote: post #345
flir wrote: post #337

Earlier quoted context omitted.

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.

One idea I've heard is prototype-first design reviews. If the cost of code genuinely trends to zero, there's no reason why most technical disagreements about product functionality couldn't come with prototypes to illustrate each side of the debate. Today, that's not always practical between token costs and usage limits.

What if the agent fucks up the better approach but does a good job of the worst approach?

Re: How the AI Bubble Bursts

#488

Post by pydry »

HDThoreaun wrote: post #472
jrflowers wrote: post #470

Earlier quoted context omitted.

> barely worse than doctors I like that this comment is below, and posted after, an example where somebody had to pay extra money to clear up a misdiagnosis of stage 4 cancer by the “barely worse” software

There are many examples of doctors misdiagnosing a wide variety of things, which is largely the point here. People think of doctors as infallible when that is not even close to true. Im certainly not saying fire all the radiologists, just advising an open mind when the actual literature starts saying that LLMs are as good as doctors in some areas.

There are many examples of people into homeopathy, chinese medicine and even witchcraft using an identical (not similar, identical) argument to the one you just used to push it.

Re: How the AI Bubble Bursts

#489

Post by ainch »

aurareturn wrote: post #139
ainch wrote: post #128

Earlier quoted context omitted.

Do you have any evidence that inference revenue is growing faster than training costs? RLVR is significantly less compute-efficient than token-prediction pretraining - especially as labs are trying to train models to achieve agentic tasks which take tens of minutes per rollout.

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.

It's definitely true that they've increased their revenue rapidly. But at the same time the 'scaling laws' that the labs were first built around require exponentially-scaling cost (10x flops for a fixed reduction in training loss).

If anything, a better look at the economics is a reason to look forward to one of them IPO-ing. I suspect the labs probably could cut R&D and turn a profit, but that might only work for one generation, until they get superseded by the competition.

Re: How the AI Bubble Bursts

#490

Post by d2ssa »

aurareturn wrote: post #171
HackerThemAll wrote: post #138

Earlier quoted context omitted.

> I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I am yet to see how a one-legged business model with just a single product (that is not crude oil), without a plan and money is going to become sustainable. Oh yeah, maybe they'll finally make money on those autonomous lethal weapons. That sounds the easiest.

Sure. I'll give you a basic plan without any insider knowledge on OpenAI. First, OpenAI and Anthropic are the leaders in model capabilities. Google is a close 3rd but 3rd nonetheless. Second, ChatGPT likely has about 1 billion active users right now. I think ads on ChatGPT will surpass even Google search ads in the future. There will be a class of users who will never pay for ChatGPT subscriptions and that's ok. Meta…

"Third, there is so much untapped revenue potential from science, medicine field that OpenAI can eventually own with Anthropic. "

Lol... yeah. They are not even looking like a going-concern long enough at this rate, let alone that.

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