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As far as business models go I think REIT for GPUs looks much more durable than Frontier Lab these days. The AI economy has a few big parts:

- Raw materials: Silicon, electricity

- Data centers: turn raw materials into compute

- Model vendors: turn compute into tokens

The frontier labs are competing in the idea that their tokens are worth more $/mtok than the others. If you look at the cost/quality Pareto curves, yes OpenAI and Anthropic are in the corner of expensive & good. But you need a log scale on price to look at these charts because the Chinese models are almost as good for a small fraction of the price. For this business model to be sustainable they need to keep innovating faster than everybody else AND for the quality difference to stay meaningful. Neither of those seem like sure things or frankly even likely to happen.

In contrast, further down the supply chain, folks supplying compute and raw materials both seem to be providing solid services that will be useful in the long term.


Nice breakdown. But data centers are increasingly responsible for their own electricity. As in Colossus.

I also barely knew Cleve directly, but his impact and insight was legendary. I got to work at The Mathworks early in my career, and the respect Cleve had was clearly deserved. Technically brilliant, but also with a keen foresight for where the industry was going and how to best serve it. RIP


I think this video does a pretty good job explaining it, starting about 10:30 minutes in: https://www.youtube.com/watch?v=S27pHKBEp30


As the first comment says "This aged like fine wine". Six years old, but the fundamentals haven't changed.


This wasn't any better than other explanation I've seen.


That was the class where I really learned how to prove things in math. Very challenging, and rewarding class.


Same


I don't think you really want a 5yo's version, because that's "computers can be smart". But for an SDE1-level explanation I made this video which has gotten tons of compliments and keeps people watching year after year:

https://www.youtube.com/watch?v=S27pHKBEp30

It's in the context of NLP, which is where transformers started of course.


"Thirty Years that Shook Physics", by George Gamow, fits the bill pretty well.


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