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The AI Demand Bubble

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Re: The AI Demand Bubble

#71
Several top level comments are attacks on the author’s credibility that do not engage the substance of the piece at all. I think the fundamental problem for people on all sides of the various debates surrounding AI is that “AI is a powerful, transformative technology” and “Anthropic and OpenAI are both doomed, and this poses risks to the broader economy” are compatible statements of fact. Just because you believe (1) does not justify dismissing (2) out of hand.

(2) is the point of this article. OAI and Anthropic are spending by far the most money of anyone in the space, as the article rightly notes, but they have no path to becoming profitable, meaning they cannot occupy that position forever. The other entities that rely on their spending to support their own margins - in this case the major cloud providers - are vulnerable to revenue collapse if OAI and Anthropic fail.

The premise most would disagree with is that the labs have no path to profitability. Two points support this: demand for inference is functionally infinite, or at least is so great that it is not meaningful to discuss its limits; and the labs are profitable on inference and are only taking losses to compete with one another. Some would extend this further and say that once the tech is good enough it will be able to drastically reduce their costs by some combination of speeding up research and creating efficiencies to reduce compute spend.

These are valid criticisms. But “AI has gotten better since he started saying ‘AI bad’” is not a reason to ignore the fact that major cloud computing providers are taking on massive new debt while becoming increasingly dependent on only two customers who face meaningful margin pressures. Unless OAI and Anthropic can find a durable moat and a means to exert pricing power, this is a serious issue going forward. That is true whether we wind up with a machine god (although we might have bigger problems in that case) or if we plateau at current capabilities.

Re: The AI Demand Bubble

#72
post #62

Earlier quoted context omitted.

If you fervently posit a theory but its predictions fail, why would anyone believe it?

Because it’s economics, a social science. Not a physics experiment you can replicate in a lab. You do what a serious person does: look at the thesis, look at the sources, look at the numbers, and do your own analysis

And you’d consider zitron a serious person?

Re: The AI Demand Bubble

#73
post #38
post #7

Earlier quoted context omitted.

unironically sama is probably one of the most honest players here after all, he is burning money and if/when they have achieved AGI they will ask it in how to make money. its a different investor incentive story than trying to monetize into profitability right now that is indeed doomed to fail against china. Having no idea but a vision achieved is rrquired to be met to have those returns is actually the honest part h…

If Altman seriously believes his role is to create AGI then ask how to make the company profitable, he should get removed from his position of leadership asap. That’s crazy territory. It’s a grift, “AGI will save us” is the same as Musk’s “Mars colony”, it’s not supposed to ever happen, it’s supposed to be a goal post they ever move further

He said the following in 2019, at a StrictlyVC event, “The honest answer is we have no idea, we have never made any revenue, we have no current plans to make revenue, we have no idea how we may one day generate revenue. We have made a soft promise to investors that once we've built this sort of generally intelligent system, basically we will ask it to figure out a way to generate an investment return for you.

It sounds like an episode of Silicon Valley it really does I get it, you can laugh, it's all right, but it is what I actually believe is going to happen”

Whether or not that’s his current view, who knows, but everyone who’s invested in OpenAI since should have known that this was at least part of his mental model.

https://youtu.be/gjQUCpeJG1Y?is=--fubVyvQnC8rgse

Re: The AI Demand Bubble

#74

Several top level comments are attacks on the author’s credibility that do not engage the substance of the piece at all. I think the fundamental problem for people on all sides of the various debates surrounding AI is that “AI is a powerful, transformative technology” and “Anthropic and OpenAI are both doomed, and this poses risks to the broader economy” are compatible statements of fact. Just because you believe (1)…

I largely agree with this take. What gives me disquiet is that I thought more or less exactly this about Uber, and was proven comprehensively wrong. Despite burning money like a furnace on an app for taxis, it seems that anyone who invested privately made a handsome return, and they are at a profitable steady state. Is AI the same?

Re: The AI Demand Bubble

#75

This guy has zero zip nada null AI background. He is a videogame reviewer and PR guy. He is a pure influencer feeding on the AI backlash he helped to create. He has been predicting a crash for how many years now? And while I can totally see Anthropic and OpenAI going through some things on the way to post-IPO FMV, those things do not include AI going away. It truly doesn't matter whether closed source Frontier lab mo…

He doesn't need AI background to commentate on financials. Your post reads like a personal attack. His record talking about stock market doesn't matter either. There is about 0 information in anyone talking about what stock market is going to do.

So his point is that big % of cloud revenue of Microsoft/Google/Amazon come from companies that:

1)are very unprofitable

2)need to raise staggering amount of capital to survive

3)are financed by their suppliers and that money is circling back to them

Your counter-argument is this:

>> It truly doesn't matter whether closed source Frontier lab models are spewing tokens or large foreign open weight models are doing it, the token factories will be just fine, and that's really all I care about.

This might be true but there are 2 majors questions here. One is exposure to Anthropic/OpenAI. If they go bust/can't IPO at expected price it's a big loss hyperscalars will need to admit. The second question is how much of that cloud revenue comes from training. This part of the demand is going shrink or disappear in the bad scenario.

Re: The AI Demand Bubble

#76
post #53

Earlier quoted context omitted.

> So in a couple years now, AI will be as gone as cabbage patch kids and pet rocks? > IMO that's anti-AI Psychosis, the evil twin of believing GPT-4o was sentient. IMO that’s a particularly scraggly straw man. Even Ed Zitron, who we can stipulate is among the most cynical, thinks that some value will be left after the bubble either deflates or bursts.

So some value, but how much value? You clearly don't like the idea there are some businesses in the AI mix that will continue making money and/or diversify their divisions to cover for any losses they suffer during this hypothetical crash or I wouldn't be getting downvoted for it. META, for example, is running a gross margin of 80% or so right now. You really think they're in trouble? So really, after all of these co…

> You clearly don't like the idea there are some businesses in the AI mix that will continue making money and/or diversify their divisions to cover for any losses they suffer during this hypothetical crash or I wouldn't be getting downvoted for it.

Me? I didn't downvote you for it and you are projecting a lot onto me without a sound basis.

Either way, my predictions are all personal, because as someone with his own problems I don't really have the spare energy to give a fuck what happens to the US economy or its tech industry. In practice for the rest of the world, I think it will all be dwarfed by the USA's failings in the Strait of Hormuz.

Though as a man in his fifties who has spent his life in the tech industry, I am slightly invested in the possibility of Larry Ellison's humiliation. Bring that on.

Re: The AI Demand Bubble

#77

I'm seeing this guy everywhere. He was on Bloomberg a day ago and then on another channel and now here. I'm curious why there are not more people like him voicing their concerns. Makes you wonder if he is completely wrong.

There’s also Michael Burry and Gary Marcus, and you can sort of infer Warren Buffett believes the market is frothy

Didn’t Warren Buffett just approve a $10B investment in Google?

Re: The AI Demand Bubble

#78
post #58

Earlier quoted context omitted.

This is the most misquoted bit in that whole fiasco. He apparently had to sell every liquid thing in the portfolio. What’s left is allegedly just some highly illiquid paper assets that they’ve also been trying to unload. The present value of those is iffy at best and may well also plummet before they can be cashed in. That “80%” can’t be realized right now in any traditional sense. No matter how you slice it the whol…

He was lucky to be managing any money at all, the West Coast smiling upon him did not translate into East Coast excitement: > When this star of San Francisco arrived in New York during his fund-raising tour around last summer, however, he received a relatively cool reception, according to three people from whom he tried to raise money, who declined to be identified talking about a private fund. They said they viewed…

Yes… the “trust me bro” vibe doesn’t play well with East Coast money

Re: The AI Demand Bubble

#79
post #2

This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…

> The actual risk that the author does not even broach upon for investors... the thing that will actually torpedo this massive investment are the open source open weight chinese models that commoditize the entire endeavor.

I disagree that "the entire endeavor" is inherently doomed for Anthropic and OpenAI. There will always be a very top end of the market running humongous models (like the recently-teased OpenAI Astra and perhaps including future versions of the existing Claude Mythos) that's too large-scale to be successfully commoditized, and that's exactly where the ongoing investments in AI datacenter compute and model training are most likely to pay off at some point. Video generation is another emerging AI area that seems to require large-scale compute, though the value proposition is definitely iffy there.

Re: The AI Demand Bubble

#80

Several top level comments are attacks on the author’s credibility that do not engage the substance of the piece at all. I think the fundamental problem for people on all sides of the various debates surrounding AI is that “AI is a powerful, transformative technology” and “Anthropic and OpenAI are both doomed, and this poses risks to the broader economy” are compatible statements of fact. Just because you believe (1)…

I largely agree with this take. What gives me disquiet is that I thought more or less exactly this about Uber, and was proven comprehensively wrong. Despite burning money like a furnace on an app for taxis, it seems that anyone who invested privately made a handsome return, and they are at a profitable steady state. Is AI the same?

The cash burn is not the problem. You can’t build a big business without it. The difference is network effects. With ride sharing apps, you need a lot of drivers and riders collected on one platform. It is nearly always better, for both drivers and riders, to switch to a larger platform. Thus, it was worthwhile to spend the money to become the biggest fish. Once this was accomplished, Uber could raise prices because switching to a smaller rival would mean less availability, and thus less utility (for riders) or less earnings (for drivers).

With AI, by contrast - at least in its current state - there is no benefit to be gained from using the same model provider as somebody else. Switching is trivial for most use cases. Since they can’t capture consumers using network effects, the labs only have the levers of price and quality to pull to acquire and retain customers. To pull the price lever, they have to reduce their revenues; to pull the quality lever, they have to increase their expenditures. Indeed, they are sowing the seeds of their own demise by making inference cheaper and more efficient: since they can’t exercise pricing pressure, efficiency gains will be passed on to the consumer, which is unsustainable if your GPU debt is priced based on yesterday’s efficiency expectations.

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