[Treesrule14]

Just to echo what you are saying, I've read the first chapter and I thought the thesis is interesting and the writing is good but I failed to be convinced becuase it makes a lot of classic mistakes you make in science. Even though logical arguments are being made there is no attempt not to overfit the data.

The author brings out a lot of stats "smart high-schooler", "effective compute", "OOM", "Test Scores", "inference efficiency" but doesn't do a good job of explaining how the author predicted these things before hand (preregistering) and how they actual will result in new technologies or how we can extrapolate past the trend line.

Also in the unhobbling section "Tools: Imagine if humans weren’t allowed to use calculators or computers. We’re only at the beginning here, but ChatGPT can now use a web browser, run some code, and so on. "

This is so non-specific (because no one has really commercialized anything with this yet) that I worry that we don't actually know if we can make the kinds of effective tools the author is talking about. Would love some feedback on these critisms

[Treesrule14]

also one funny thing is that the author mentions power constraints, but then doesn't calculate how many terraflops for example the us grid can produce etc.

[zooq_ai]

That's where the Trillion $ cluster comes in. It also includes building power plants, not just data centers

[ml-anon]

That’s around the time he says we should build 1200 shale wells in Pennsylvania.