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How the AI Bubble Bursts

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Re: How the AI Bubble Bursts

#91

Post by albinn »

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…

I would think that we are going to see RAM prices increase even more, given, among other things, pure helium disruptions and increased electricity prices.

I haven't looked closely into TurboQuant, but perhaps it will revolutionize just as much as the 1-bit llm did...

Re: How the AI Bubble Bursts

#92

Post by aurareturn »

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 advance if you're an AI company.

  OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them with the more profitable corporate customers and software engineers.
AI bubble is bursting because OpenAI is trying to monetize free users on ChatGPT with ads but Anthropic is kicking butt in AI. What kind of logic is that? So it seems like AI can be monetized as Anthropic shows. Is AI going to burst because OpenAI can't monetize but Anthropic can?

  I wouldn’t be surprised at all if in the next couple of quarters we see OpenAI looking for an exit. It will be interesting because the sizes are now so big that we will probably know all the details. The most likely buyer is Microsoft, they already own a lot of it, and because of that, they are the most interested in showing a win.
I'll take the opposite stance. I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I think Anthropic and OpenAI are going to run laps around current big tech except maybe Google. For example, in a few years, I think AI agents could completely replace Microsoft Office, Microsoft's cash cow.

  Independent reports state that Claude metered models are priced 5x more expensive than their subscribers pay
Already dispelled. It isn't 5x more expensive than their subscribers pay. Inference has a gross margin of 50%+. It's been repeated over and over again by Anthropic CEO, OpenAI CEO, and just about anyone who's done deep analysis on token profitability. If you don't believe OpenAI and Anthropic CEOs, just look at inference providers on Openrouter. They don't have VCs backing them selling tokens at a loss. They should be making margins on every token in order to keep the lights on.

Re: How the AI Bubble Bursts

#93

Post by iterateoften »

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…

According to open router token demand is growing at something like 10% a week

It’s insane

Re: How the AI Bubble Bursts

#94

Post by nyeah »

paulddraper wrote: post #87
boriskourt wrote: post #48

Earlier quoted context omitted.

> The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. > For the data center build outs, demand for tokens is still exceeding supply. Can you provide any numbers for this?

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.)

Can you give a few penciled numbers?

Re: How the AI Bubble Bursts

#95

Post by baq »

schnitzelstoat wrote: post #28

It's a winner-takes-all market and everyone wants to be the next Google and not the next Lycos or AskJeeves etc. It'd be interesting to see what they spend all the money on though as we seem to be hitting diminishing returns and I'm not sure if the typical enterprise user really cares about small improvements on benchmarks. It seems like it'd probably be better to spend all that on marketing, free trials, exclusivity…

> It's a winner-takes-all market and everyone wants to be the next Google

absolutely isn't! if billed per token, there is no reason to be married to a single model family provider at all. the models have very different strengths and weaknesses, you should be taking advantage of this at all times.

Re: How the AI Bubble Bursts

#96

Post by hirako2000 »

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…

Not crashing yet. The article is looking 1 to 5 years to come.

Given Nvidia's CEO's agitation I would give credit to the prediction, and if it's correct the price will go back to what it was, or even lower of investment in capacity are made today.

Re: How the AI Bubble Bursts

#97

Post by amelius »

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…

> 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

Re: How the AI Bubble Bursts

#98

Post by pier25 »

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.

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

Re: How the AI Bubble Bursts

#99

Post by 56745742597 »

A_D_E_P_T wrote: post #51
general_reveal wrote: post #15

Earlier quoted context omitted.

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. Som…

[dead]

Re: How the AI Bubble Bursts

#100

Post by chrisweekly »

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…

> "decades of overinflated engineering salaries"

'Overinflated' relative to what? You make some good points but I don't accept this as a premise.

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