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Comment by compiler-guy | Hacker News Reader

"The underlying product, the model keeps improving and therefore increases its value."

That's not exactly true. Yes, the fundamental capabilities of the models do seem to be growing dramatically, but the economic value of any particular model may be steady, or even falling, because of commoditization, or other issues external to the model itself.

Without a moat, improvement in model capability does not necessarily translate into economic value--and the labs need economic value to pay their obligations.

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The economic value may be real but the profits may not be.

One thing that's clear is that there is no leading vendor in this space and there may never be one. To some extent premium models can charge a premium price but it's going to be a competitive market and the likes of Anthropic and OpenAI will not be able to sustain monopoly pricing.

100%. I have sometimes wondered if China is playing the long game with the open weight models trying to tank the margins of the US labs so these profits don’t materialize and the US economy (currently predicated on the net that they will) suffers. I think this is a coherent strategy beyond just “don’t let the US control AI as a strategic asset.”

It's the domestic policy version of "commoditise your complement".

The AI debate has often been flattened into "Do you believe in the long term viability of the tech?" when there is also another question that needs to be asked in "Do you believe in the long term viability of these companies' business models?" It's a lot easier to believe the former than the latter.

It's entirely possible for this tech to be humanity altering in the long term while we are also in a huge bubble that could pop at any moment. In that way the housing analogy is apt. The utility of the houses themselves didn't change, the problem was purely with financial markets until eventually those markets made it everyone's problem.

As of now the compute is fully utilized, progress is rapid, and both OpenAI's and Anthropic's revenue is growing fast.

This could change, but there is no sign of it yet.

No one knows whether other companies are going to catch up, with what compute, or if OpenAI or Anthropic will be able to conquer robotics or medicine.

Yes exactly the same as during the Dot com bubble.

Having lived to adulthood before Amazon started, I remember the massive debt to profit ratio of many dotcom companies.

Most importantly, I stick to Amazon's lesson: Sometimes, it's not about who's first. The winner can be determined by who's left.

Notably a lot of those companies went down, a lot of investors lost money, but the internet and e-commerce proved to be just as big as people expected back then, maybe even bigger.

Yes I that was in reply to OP making similar point about AI

Almost, but not quite.

Consider

https://www.ft.com/content/6f3ada65-c56c-499c-8eb6-008fac589...

I hate to say it, but the reality (AI, today) might be closest to PG's "intuition",to wit, it doesn't pay to be left of center-right

For "previous bubbles", I have a different, apolitical,take

That is much less of a systemic issue though. It could kill OpenAI or Anthropic, but it wouldn't render these large GPU data centers obsolete since whatever replaces them, be it open models or cheaper closed models, would probably still require a lot of GPU compute.

Less bad, yes. But still bad. There will definitely be demand for the compute, the question is whether it will be enough to keep the value of it at the levels you’d expect if the tenants were in a monopoly/duopoly world. Competition puts downward pressure on margins and that’d translate into pressure on data center leases.

Could put pressure on data center margins, but not revenue, and not necessarily gross profit.

"probably still requires a lot of GPU compute" is something that would be very desirable to undercut.

There's a galaxy of potential AI markets that are local-only for compliance/privacy/deployment environment reasons, and an equally large and overlapping set of use cases where you won't be able to bolt a rack of thousand-watt GPUs on the side of the device.

What if the next "DeepSeek shock" is something we can run for non-toy use cases on our box of old Android phones? The GPU data centres could be expensive albatrosses very quickly.

There's probably a case that right now, the bigger-is-better paradigm protects incumbents-- a smaller model will always have a FOMO factor unless it can be proven competitive, so that leaves the playing field to those who can afford to train and deploy a new Fable or Sol every few months.

As the model keeps improving, to the extent it has some utility, it will decrease in value.

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