Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

How the AI Bubble Bursts

martinvol.pe

Post reply on HN
Print view View original

51–60 of 557 posts

Re: How the AI Bubble Bursts

#51

Post by A_D_E_P_T »

general_reveal wrote: post #15
myspy wrote: post #9

Earlier quoted context omitted.

Why?

You have to be uneducated to even read an “AI is bubble article”. Anyone working this stuff knows how much more compute we need.

Two things can be true at the same time:

- AI is a genuinely transformative technology on par with the internet and on track to probably surpass the smartphone

- The inflated valuations, the circular flows of money (or "money"), and the financial cup-shell game mean that the players of the game are all a few bad weeks away from catastrophe. This is, of course, nothing new for SV -- but the scale this time is new. Some believe it will soon collapse -- "bubble," thus.

Re: How the AI Bubble Bursts

#52

Post by malfist »

infecto wrote: post #30

It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the…

> The cost to serve tokens is absolutely profitable today

How can you possibly say that? Everyone knows that's not the case, these companies are losing money every day selling tokens. Revenue is not the same thing as profit.

Re: How the AI Bubble Bursts

#53

Post by joshstrange »

> 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 fact this article links there with text "RAM prices are crashing" throws the entire rest of the article into doubt for me.

RAM prices are most certainly not crashing (yet) and treating it as a forgone conclusion because _one_ lab found gains could be made and hasn't even reported on the efficiency of their method is just irresponsible. It's almost as bad as when LLMs link things to prove their point, you visit the link, and find it says nothing of the sort or even the opposite.

[0] https://pcpartpicker.com/trends/price/memory/

[1] https://tech.sportskeeda.com/gaming-news/how-google-s-new-tu...

Re: How the AI Bubble Bursts

#55

Post by est31 »

mrbungie wrote: post #27
nopinsight wrote: post #11

> nobody is sure if even their metered pricing is profitable This is most likely wrong. Lab executives insist that serving tokens is profitable. It's the cost of training next-gen models that requires them to keep raising ever larger rounds. More importantly, many independent providers price tokens of open-weight models at a fraction of Anthropic's prices.

> Lab executives insist that serving tokens is profitable. Maybe marginally profitable, but right now they need to give out subsidies for people to use their products (Antigravity, Codex, Claude Code et al) in an actually useful manner that prevents churn and at the scale they need to justify usage growth forecasts, which they need to keep the wheel turning. Probably if you look at the users who exclusively use the s…

It's a loss leader but this is normal. Same has happened with Uber, Airbnb, Amazon, etc. Using VC money to buy marketshare and once you have it, you can milk it.

The question is more around the moats that these companies have and it seems to me while their models are amazing technology, they don't really have a moat. The open/chinese models still continuously catch up to the american ones.

Re: How the AI Bubble Bursts

#56

Post by SirensOfTitan »

infecto wrote: post #30

It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the…

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 were paid what they were worth. Software is or was one of the few remaining arenas wherein a person can find a middle or upper middle class lifestyle consistently.

I will also note: a startup raising an 8 MM series A and eventually fizzling out is not the same at the hundreds of billions invested in these AI companies without a path to profitability. It is utterly absurd to pretend these are the same thing: any company ingesting that much cash needs to justify its capacity to survive.

Re: How the AI Bubble Bursts

#57

Post by yorwba »

dash2 wrote: post #26
sunaurus wrote: post #17

Earlier quoted context omitted.

The point is that you can’t just serve tokens without also training the next models. It’s an inseparable part of your costs, so naturally you can’t be profitable unless the price you are charging ALSO covers training.

Is that right? I think that you can serve tokens without training the next models. It would be bad strategy, but it would work. So it's an important question, are they covering their operating expenditure? If they are the business has legs (and it will be worth spending a lot to train the next models). If not, maybe not.

There are companies that already do nothing but serve tokens using models trained by others. Just running infrastructure and collecting a reasonable fee for their troubles. It's only a bad strategy if you want to claim to investors that you'll gain monopoly market share if only they could give you a few more billion dollars.

Re: How the AI Bubble Bursts

#58

Post by Aperocky »

infecto wrote: post #30

It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the…

Demand of tokens is absolutely skyrocketing.

And unlike the traditional "this will replace humans right away", I think what this introduce is a lot of incentive to spread those token in places where there was never any incentive to hire a software engineer for previously. In turn, that will drive a lot of business activity in those area that will potentially fail given the current quality of the output.

This feels like a boom before bust scenario, and I'm not even sure if it will bust.

Re: How the AI Bubble Bursts

#59

Post by beepbooptheory »

baq wrote: post #32
atwrk wrote: post #20

Earlier quoted context omitted.

But are they actually profitable, or do they employ creative accounting where only parts of overhead expenses are counted against all of inference revenue, similar to what Uber did? OpenAI's numbers show that they definitely are not profitable on inference, and even worse, revenue growth scaled linearly with inference cost from 2024 to 2025, which means they can't outgrow this problem. See https://www.wheresyoured.at…

If they shut down all training today they’d be absolutely printing money for the next couple quarters and then die with a bang once the other lab releases the next frontier to the public.

I don't really get the last bit. It's hard to imagine what a new fangled "frontier model" could do that would blow anyone out of the water. Like what does this look like? Really good benchmarks? Who cares about that anymore?

Re: How the AI Bubble Bursts

#60

Post by Aurornis »

This article tries to build upon a lot of half-truths or incorrect facts, like this:

> OpenAI is struggling to monetize. They turned to showing ads in ChatGPT,

The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new.

The discussion about being unprofitable also repeats the reductionist view that these companies are losing money and therefore the business model doesn’t work. This happens with every VC cycle where writers don’t understand that funded companies are supposed to lose money while they grow. That’s what the investment money is for.

We have very strong indicators that inference is not a money loser for these companies and is likely very profitable. They should be spending large amounts of money on R&D to get ahead and try new things while they’re serving up tokens.

The “but they’re losing money” argument never seems to be brought out against competitors that literally give away their models for free and for which we can calculate the cost of serving 400B-1T parameter open weight models.

Post reply on HN