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How the AI Bubble Bursts

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Re: How the AI Bubble Bursts

#301

Post by WarmWash »

naravara wrote: post #136
pier25 wrote: post #98

Earlier quoted context omitted.

So these companies will be profitable if training stops? Is that even a real possibility?

The impetus to continue training at the pace they are is driven by the competition. So if the money starts drying up, then they’ll naturally slow down because they’ll have to figure out how to do more with less. I suspect that once the models hit a point of “good enough” for certain use cases companies will start putting R&D focus in other areas that may be less expensive. Like figuring out how to run more efficientl…

What's interesting to note is that the "intelligence" labs can squeeze out of an H100, an almost 4 year old GPU, is dramatically higher than what they got out of it in 2022.

It hints that once these labs get a good enough "everyday model", they can work on efficiency so they can serve these models on old hardware. Which is almost certainly already happening.

Re: How the AI Bubble Bursts

#302

Post by hirako2000 »

classified wrote: post #263
vekker wrote: post #251

Earlier quoted context omitted.

> Seriously, what value are tokens providing other than justifying layoffs Like the OP said, it's incredible how polarizing this debate is. When I read comments like yours, I feel like a significant part of the global workforce in IT must be living on another planet? Or they never really used Claude Code, Codex, OpenCode, ... intensively before because of company policies? I legitimately am at least 10x more producti…

> 10x more productive That claim is totally worthless without you providing concrete information how you measured that.

And that's my point about value. That engineers can spit out far more code, or that they don't have to think much is surely precious convenience.

Value add so far lacks evidence.

Layoffs. It justifies them to the public. I'm not certain it grants them as it contradicts a principle of enterprise: scale, as much as you possibly can.

If tokens provided value today, we would be hiring more engineers to review their output and put things together.

Re: How the AI Bubble Bursts

#303

Post by [deleted] »

tapoxi wrote: post #266
piker wrote: post #144

Earlier quoted context omitted.

There are some frustrating parts, but subpar is an odd way to describe GitHub to me. I’m pretty happy with what they’re doing, and find the UX super helpful. I do agree Actions needs a debug mode but otherwise I get a ton of value out of the service for $20/month?

Specifically their failure to meet reasonable uptime requirements. I can't run a 99.9 service on a 99.0 platform.

[deleted]

Re: How the AI Bubble Bursts

#304

Post by kmeisthax »

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…

I thought we were going to hit token saturation years ago, but they keep inventing new ways to use tokens. Like, instead of asking a chat model to write something and getting ~1000 tokens out of it, you now have an agent producing ~10,000 tokens - or, worse, spawning 10 subagents that collectively burn ~100,000 tokens. All for marginally better answers with significantly higher compute usage.

Personally, I would have used all those tokens to generate synthetic data for IDA (iterated distillation and amplification) so that the more efficient 1000 token/answer chat model can answer more questions, but apparently that doesn't justify an insane datacenter buildout.

Re: How the AI Bubble Bursts

#305

Post by vbarrielle »

iterateoften wrote: post #129
thereitgoes456 wrote: post #50

Earlier quoted context omitted.

> The cost to serve tokens is absolutely profitable Can you explain why you know better than the analyst at Cursor cited in this article?

Open router is an upper bound of compute cost for the open source models. So people assume that opus and sonnet really isn’t sucking up 10x the resources because open source models aren’t 10x worse. Idk if it’s true or not, but haiku is $5/m tokens and it is much worse than the $2-3/mt models imo

Openrouter is a startup, what's the indication it serves token at a profit? It could be serving them at a loss to show growth.

Re: How the AI Bubble Bursts

#306

Post by hirako2000 »

Throaway1975123 wrote: post #292
vekker wrote: post #251

Earlier quoted context omitted.

> Seriously, what value are tokens providing other than justifying layoffs Like the OP said, it's incredible how polarizing this debate is. When I read comments like yours, I feel like a significant part of the global workforce in IT must be living on another planet? Or they never really used Claude Code, Codex, OpenCode, ... intensively before because of company policies? I legitimately am at least 10x more producti…

I created 5 websites this year and am working on 3 prototype games. For free. Without any knowledge of coding beforehand.

Value?

There are millions of other wanna be engineers doing exactly the same, assuming demand will scale as much as the offer.

What returns are you getting on those?

Let me create 500 websites, deployed for free, I hand that over to you by end of day. Will you give me a cent per piece? If so, happy to do business with you.

Re: How the AI Bubble Bursts

#307

Post by wavemode »

H8crilA wrote: post #295
wavemode wrote: post #269

Earlier quoted context omitted.

tbh I don't think this use case is going to be as big as people seem to think there are a lot of reasons, but in brief - I think AI desktop use is a product that the average person isn't going to get much value out of. to make an analogy - the creators of Segway thought people would buy them in large numbers, but it turned out most people don't mind walking manually (or at least, don't mind it enough to spend money o…

I was thinking more remotely managing the computer in a warehouse, replacing the mouse of an architect, or some physical object engineer. That your grandma can finally find Discord by speaking to such a bot is just a nice side effect.

well yeah I wasn't even talking about professional use, since I think in professional use cases it will turn out make a lot more sense to set up APIs that AIs, use, than to set up screen scraping and mouse+keyboard use.

in fact even in rare cases where it's not possible to get an API or CLI to interface with some piece of software, I think people will find that their best bet is to first create a deterministic screen-scraping program for that specific software, then have that program serve an API for the AI to use. it would be so much cheaper to run (inference-wise) and so much more reliable, than having the AI itself perform the image interpretation and clicking.

I see AI desktop use as mainly a consumer product for that reason, since that's the situation where you have to react "on the fly" to whatever the user asks you to do and whatever program happens to be on their computer (versus professional cases which are more large-scale and repetitive, and where you can have a software developer on hand).

Re: How the AI Bubble Bursts

#308

Post by win311fwg »

keybored wrote: post #298
9rx wrote: post #253

Earlier quoted context omitted.

> Salaries across industries in the US have remained flat since the 1970s What do you mean? The real (meaning adjusted for inflation) hourly wage in the US has increased by around 20% since 1970. What has changed since the 1970s is that wages are no longer coupled to productivity. Perhaps that is what you are thinking of? But that should be an obvious truism for anyone in tech. We create the very things that cause th…

> We create the very things that cause that to be the case! What happened in the 1970’s was the NeoLiberal shift and wasn’t caused by software.

That NeoLiberal shift did not take place in a vacuum. It was a product of the world around it. It absolutely was caused by tech.

If we — those with the power to build the productivity creators — took a stand and said "we refuse to create tech for the interests of the few" it would have never happened. But, instead, we welcomed it and are responsible for it.

Re: How the AI Bubble Bursts

#309

Post by strangegecko »

drakythe wrote: post #195
paulddraper wrote: post #87

Earlier quoted context omitted.

Anthropic has said inference is profitable. That’s a biased source, but the math pencils. This is why switching to local open weight models saves a lot of money. (Even though it’s not apples to apples.)

Anthropic also recently tweaked their usage limits to discourage use during peak hours. Why would they do that if inference was profitable?

Profitability doesn't imply infinite ability to scale. Of course they will want to prioritize their most profitable customers when they hit capacity issues.

Re: How the AI Bubble Bursts

#310

Post by marcyb5st »

gruez wrote: post #296
marcyb5st wrote: post #288

Earlier quoted context omitted.

Isn't salary a proxy of how hard to replace one person or a group of persons is or how valuable they are? There was a surge in demand for SWEs and scarcity brought salaries up. Are them too high? Hell no. On average, my colleagues and me generated ~2M$ each in 2025 for our company, while we get payed a fraction of that (grants and bonuses included). If you look at net income per employee we are at around 700k each in…

>There was a surge in demand for SWEs and scarcity brought salaries up. Are them too high? Hell no. On average, my colleagues and me generated ~2M$ each in 2025 for our company, while we get payed a fraction of that (grants and bonuses included). If you look at net income per employee we are at around 700k each in 2025. So by that logic, housing in coastal cities also aren't "overinflated"? After all, like SWEs, they…

Maybe we give different meanings to the overinflation word. I see it as something that is speculative/shady in nature. Is housing overinflated? Probably in some places for sure because those who already have a house or invested in real estate wants to cut down supply to raise prices.

Is the same on the job market? I don't think so. I never heard any SWE saying "let's scare people away from a CS career so we can bargain for higher salaries". The opposite is true though. Companies participate in career fairs, pre-uni events to make people gravitate towards a CS careers, ... so with a higher supply each employee loses a bit of bargaining power.

Small excursus, this very fact was taken to the extreme in 2022 when everyone did layoffs at the same time despite the numbers being still great. If you put 300k people on the street at around the same time you can hire some of them for way less money as they now lost all leverage (since there are other 299.999 people waiting in line for a job).

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