Early last month, Leopold Aschenbrenner released a long essay and podcast outlining his projections for the future of AI. Both of these sources are full of interesting arguments and evidence, for a comprehensive summary see Zvi's post here. Rather than going point by point I will instead accept the major premises of Leopold's essay but contest some of his conclusions.

So what are the major premises of his piece?

1. There will be several orders of magnitude increase in investment into AI. 100x more spending, 100x more compute, 100x more efficient algorithms, and an order of magnitude or two gains from some form of “learning by doing” or “unhobbling” on top.
2. This investment scale up will be sufficient to achieve AGI. This means the models on the other side of the predicted compute scale up will be able to automate all cognitive jobs with vast [...]

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Narrated by TYPE III AUDIO.