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I think this is a good casual introduction to the marketplace dynamics of how ML will impact the market. I do, however, disagree as this version of things assumes a more open-information set of competitive strategies among potentially ideal agents from a game theoretic perspective, and we can see this is absolutely not the case 'in real life'. To one of his examples -- Exxon-Mobil.
An updated version: There will be a log-normally distributed set of winners and losers from the exponential effects of ML and 'AI', and the flatness of this curve will be almost entirely solely determined by the governance of the various countries in the world over different economic and/or informational policies. Other than that, the information asymmetry is going to make it a power-bloodbath as we go through our informational-industrial revolution.
While I'm here, I think Hotz does contribute a lot of good to the field, though I do have a bit of a minor personal beef with him. He said he was going to reimplement https://github.com/tysam-code/hlb-CIFAR10 in tinygrad, bashed a few parts of the code for a while on stream, and then gave up a few hours later because of the empirical speed/occupancy numbers. >:( I want my fast reimplementation, George.
lol, you should see me bash my own code. I'm even more mean.
https://github.com/tinygrad/tinygrad/blob/master/examples/hl...
have a bunch of bounties on it, we're getting 94%+ now! mostly not me who wrote this, see history. have to switch to float16 and add Winograd convs still. we have a branch with multigpu too.
goal is to beat an A100 in speed on a tinybox.