Big red flags that I think point the other way:

- anthropic IPO repricing

- pareto frontier gap decreasing by the month between open and closed models

- SpaceX disappoinment

- enterprise buyers as main consumers of closed tokens are being displaced by OS competition for pennies

- job loss and entry level hiring collapse

- massive discounts of current data center contract debt

- consumer open weights model efficiency improving constantly

- the Chinese arms race

- a possible rapid downward spiral that may force governments to step in and subsidize

Am I missing anything?

- revenue growth at Anthropic slowing

- margins shrinking at Anthropic

- Google getting thwacked by missed earnings

- OpenAI missing funding target

- price war

- Microsoft revising capex projections down

- Plateauing of model capability improvement

What's weird to me is that you don't see a lot of people making deals that seem way too good to be true but yet the total numbers are absolutely gigantic. Throw on the fact that the stranded assets will have a shelf life, it really seems terrifying. Yet everything is being priced as pretty darn risky. I think maybe there can be a big slowdown without a dramatic pop. A sort of grind down. But there's not a lot of room for error to prevent a pop so I guess it will happen? I don't know its very weird.

Also of course this is all predicated on models not making another dramatic leap. The signals out of the cutting edge labs don't really suggest they have a model that would be as dramatic of a leap as Mythos was when it came out in the hopper. Their code quality seems about as mediocre as what the publicly available models can do. The OpenAI math results are very impressive but that's ripe picking for AI. Also they keep talking about a coordinated training slowdown which is textbook antitrust so they seem to want the government to force their hands off the "spend money on R&D" button.

So I don't really know. I guess I would say purely on vibes that this doesn't feel like a bubble but the size of the build out is just so massive that there really isn't a big window for a success case.

The biggest metric is that anthropic make ~$2 for every $1 of compute.

Two things:

1) it requires a massive money pit to make that compute worth anything

2) it requires charging a premium price

To compare to two previous bubbles; railways in the UK and USA.

running trains was really quite cheap and engines weren't expensive per passenger served. Compared to stage coaches, the number of staff needed was < 50%. the Massive fucking problem was that it needed GDPs worth of money to make the railway in the first place. Moreover as more railways were put in it significantly altered profitably of railways near them. Lines that were there for produce moving suddenly lost profitably because the produce they were moving fell out of fashion

Big enough companies who could be the best customers can run models on their infra for a fraction of the price. Eg: Revolut.

https://dealroom.co/news/169124-revolut-moves-2-000-engineer...

Inflation, house prices, gas prices, interest rates, huge public distrust of government and corporations, votes to restrict data center construction, endless war in Iran, etc.

- job loss and entry level hiring collapse --> I will out that as in the group "Not a bubble" (Not that I am thinking it myself that it's not a bubble).

It looks like the end goal of replacing labor by capital is working.

Political resistance against data center build-outs

I generally agree with you, but have to get this off my chest.

> pareto frontier gap decreasing by the month between open and closed models

We need a temporary moratorium on the words "pareto frontier". Every new model is the pareto frontier by some combination of metrics. Like "Bayesian Priors", people love saying / tweeting it because it sounds Smart.

It's like watching car commercials where every single vehicle has won something from JD Power and Associates. Which, (a), who the hell are they? and (b) you can only pass out so many awards until the gluttony of awards proves the award is worthless.

This isn't targeted to you! It's a pet peeve.

Also - all the gee-whiz AI companies are headed by people who don't have great business backgrounds, either by people from tech backgrounds (chasing the last of the VC), or by people with the kind of "interesting" background who you wouldn't lend your own money!

Maybe this is what you meant by "Chinese arms race" but there is, though not quickly, a massive wave of increased hardware supply incoming. Again, let me mention this isn't coming soon in terms of the AI bubble conversation. But China is pushing for a home grown EUV and fabs that should start coming online and having an impact in 2030.

The reason that is important is it will fuel the competitiveness of on premises and local open weight models.

Though maybe it's less useful in the "bubble" conversation since over four more years you could fit in various booms and busts before the supply side significantly starts changing.

As the friendly article points out, the "AI is a bubble" hypothesis and "entry level hiring is collapsing because AI is replacing their jobs" hypothesis are not really compatible.

As always, reality is likely a muddled mix: there is real utility and there is wasted investment that will never pay itself back.

Musk's claim of Softbank defaulting on turbine orders for datacentres.

unless I am mistaken, you missed that the datacenter infrastructure being a one-time cost. nope. those servers have about a 5 year lifetime and then are likely to be replaced. The buildings aren't the expensive part. The GPUs are.

so I think that's one big miss from this blog, or I don't understand datacenters as well as I think I do (which is always a possibility! hopefully someone will inform me if I am wrong)