[Driver4732]

If you read more of Zitron's work, he says that there's little demand for the AI compute power outside of OpenAI and Anthropic. If they are bled dry, then the hyperscalers will not have enough customers for the data centers which they have blown so much capex spend on and will have to soon go into debt to ensure they can be built. The GPUs and the high bandwidth memory they use have little use other than to run and train these LLMs.

[jay_kyburz]

> little demand for the AI compute power outside of OpenAI and Anthropic.

I think every other business is going to slowly wake up to how powerful machine learning can be, and or, how important it will be to run your own models you can trust.

I don't doubt that there is a bubble, but once the hardware is built, there will be plenty of customers.

I guess if you overpay for hardware, you can be undercut by data centers built after the bubble pops, but that might just mean your return on investment is slower.

[Driver4732]

I don't think so. AI is a general purpose tech and you have many companies still doing discoveries on how to apply the technology in a useful way. It's an expensive solution in search of a problem. Not to mention no one wants to pay the actual cost of what it takes to deliver the technology. The whole business model is unsustainable.

[jay_kyburz]

Go have a look at that Seedance thread. Movies and TV will be completely AI in the future.

[bdangubic]

and he wrong on all of those accounts. but he’s got the best gig, he has been writing literally one same article for years, gets LLM to shuffle the words and publishes it under a different title :)

[jsnell]

Now, now, let's be fair. I don't think LLMs are used for writing or editing the articles in any way.

(Each reader can decide themselves whether what you wrote is unfair to Zitron or to LLMs.)