The AI bubble is popping; we just don't know it yet

> infrastructure that looks increasingly unneeded

This is the crux that needs to be substantiated. Without substantiation none of your other arguments hold up.

It's holding up the entire US stock market and therefore the entire US economy and the dollar value. You probably don't want this particular Atlas to shrug.

Anthropic is almost purely a model company. They own close to no data centers.

If models are becoming commodities, and the main bottleneck is actually serving them at scale, Anthropic does not appear particularly well positioned.

If AWS had a ~60-80% margin for decades, I see no reason why inference can't have a ~60-80% margin for quite some time.

The problem is, if costs continue to drop ~90% for the same level of quality every 18 months, demand is unlikely to grow 10x to keep the revenue stable.

Who knows. Jevon's paradox. But the cost/quality is dropping too fast that it's hard for me to imagine demand keeps up long term to keep revenues (and profits) GROWING.

More and more companies are signing up with OpenAI and Anthropic at near exponential growth to automate everyday tasks. If anything, these two should manage to IPO just fine. The rest of the downstream startups probably won't make it.

The trick the frontier labs have done is define AGI as "better than humans at the vast majority of valuable knowledge work" which is definitely not what most people think it means.

Even if we agree with this take (and I do think it's a likely take that you're right on the long term), it doesn't change that it seems likely we're in a bubble, and it probably will pop.

We see a similar paradigm with lots of revolutionary technology. The initial promise is high, people get very excited, lots of money pours in, and.... 15-30 years go by before we start seeing real impact across the economy at large.

It's just a real slog to actually implement and roll out new tech.

So take robots: I can promise you that you won't see robotics in every household in the next decade (especially so if we exclude the current market of robot vacuums). Even if a company makes an incredibly capable robot "today" (and to be clear - they are not) it won't have time to scale out production, reduce costs, generate a used market that's accessible to less wealthy consumers, deal with regulatory hurdles and quality problems that only pop up in real-world usage, etc...

It's just slower than you're implying.

The change very well will happen (I'm inclined to agree that things are going to shift). That doesn't mean that the current investment is sane and will pay off.

So many historical examples of this, just two here real quick:

- Ford built his first automobile in 1896, founded a company in 1901, went out of business, got sued by ALAM, didn't build more than 10k Model T's until 1910, then only finally hit real scale (of low hundred of thousands of units) in 1913: More than a decade to "basic scale". Household ownership didn't hit 60% until 1929... 30+ years later.

- The initial web enthusiasm, followed by the dot-com crash in early 2000s...

Robotics in the household has been the realm of science fiction for decades and it still hasn't happened. We get dedicated, compact machines like dishwashers and washing machine/dryers, that's it. Most recent innovation has been the automatic vacuum.

If you want someone else to do household chores, hire someone. You can pay someone to do your house chores for years for the cost that these things will have initially.

> I would argue we still have not even really gotten started.

I agree, but that doesn't mean there isn't a bubble.

It is possible we'll have all those changes and they generate a lot of revenue for very few players but, still, a lot of the remaining players fail.

In particular, I worry about robotics. It is clearly becoming a China-only game. The west just doesn't have the industrial manufacturing critical mass to play it.

Yep, that is what the bet is. The build out will continue, even if it looks different.

The Internet was a 'bubble' at one point, and after it crashed in 2000, it didn't go away, it continued to build out. We're still using the Internet after the Internet bubble popped.

This is something I have been pondering recently. If I compare the cost of a plunger ($23.99 on Amazon) to a median plumber salary ($62,970 per year per BLS), the difference is orders of magnitude. This feels like a gap that needs to close. I suspect plungers are too cheap right now but will raise their prices to a point where only big companies will be able to afford subscriptions to use them. I think soon we will seen plungers that are only sold at very high prices.

Open weight models tell a different story. Inference is not that much more expensive than what a 100$ plan would allow and will only get cheaper (for current capability models of course, frontier not so much).

Also, something else to add. At first I thought no one wants to build data centers in hotter areas in the middle of deserts (many places in the American continent). So nobody would spend money building a data center in the Chihuahuan Desert for instance. However, a game of latencies will either require cover llm access from these areas, or make people move closer to the other data centers. In the former, llm prices will go up; in the latter, there will be a migration towards data centers that increase the price of the areas around.

LLMs are not as cheap on enterprise plans.

I don't understand this argument.

Go to OpenRouter and look at all of the unsubsidized providers.

> 100k/year to 200k/year

Is this range just Silicon Valley or what is this? Even including just Europe, you're looking at a lower bracket of 10k. If you expand to the rest of the world... Or do you think rich cities in the USA, where developers make 100k+ per year, can alone sustain this industry?

It is. However remember that when the bubble pops it all works in the reverse direction too. Suddenly you have to mark down investment losses, missed revenue, and written off commitments.

Companies can go from looking really good to a complete financial mess almost overnight when all that leverage and self-reinforcing stuff unwinds. See last weeks headlines for one such scenario.

It's entirely possible China has a little bit of a bubble too when it comes to development investment vs demand. But obviously the bubble in the US is basically a whale compared to whatever small fish China is.

I expect Nvidia to survive the crash on its own, and everyone else except Softbank to be bailed out with US taxpayer money.

> but... as for google's bots... you need your website to be on the Google search results...

Why? Depends totally on what kind of website you are running.

> well if bubble pops, everyone will die EXCEPT google

Also, possible Apple since they haven't gone into deep debt to finance 'AI buildout'.

This is poorly stated in the podcast, but the underlying point is correct: while cost-per-token is going down, overall token use is way up. This is causing the cost of using LLMs in corporations to skyrocket.

Of course, the price of tokens going down makes it cheaper. You can now afford to throw millions of tokens at solving a problem that would have been impossible for AI to solve at all a year ago for any price.

People completely lack imagination about this stuff. The main problem right now with AI isn't even AI successfully producing code at a reasonable cost, it's human coordination and review that is the bottleneck.

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