Clive Chan
2.3K posts

Clive Chan
@itsclivetime
perplexity per picojoule @openai / formerly a car @tesla dojo


Reading the encyclical, I am reminded that the Vatican is fundamentally a city-state on the continent of Europe, and that its elites, which of course include the Pope himself, cannot resist the myopic preoccupations of the Eurocrat. This document would be much improved if it were less enamored of the traditional academia/civil society talking points on AI (“The apparent objectivity of the responses and suggestions these systems provide can lead us to overlook the fact that they reflect the cultural assumptions of those who designed and trained them” woah! really???) and more engaged with where AI is headed. But instead of doing that, the encyclical dodges in the deepest sense, denying that AI “really thinks” or “really learns” and all that typical strain of cope that amounts to magical thinking: “when a computer does it, it is ‘data processing,’ beep boop, but when a human does it, it is ‘actual learning’” It is probably actively bad for global understanding of AI that the Pope endorsed this viewpoint as late as 2026. In the end, this encyclical reads to me as though ghost written by the blob of Western civil society, the same people whose feckless and incoherent preaching we have heard blanketing our media for decades now. And, in a very important sense, it was written by them; after all, who forms the peer group for the elites of a European city-state? Like that blob, the encyclical is intellectually flaccid at its core, no matter how well intentioned it may be. This document is a missed opportunity to advance global understanding of AI, and yet another blow to the legitimacy and sanctity of storied Western institutions. As if you needed one more.







So average days between releases is 52 days, if we exclude the first long one, it is 40 days. So a couple of weeks at least is a reasonable bet. Could be a bit longer if it is a new pre-train and they need more time to adjust.

New blackboard lecture w @reinerpope How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 0:00:00 – Building a multiply-accumulate from logic gates 0:16:20 – Muxes and the cost of data movement 0:25:59 – How systolic arrays work 0:39:00 – Clock cycles and pipeline registers 0:51:40 – FPGAs vs ASICs 1:03:14 – Cache vs scratchpad 1:07:16 – Why CPU cores are much bigger than GPU cores 1:11:49 – Brains vs chips 1:15:22 – A GPU is just a bunch of tiny TPUs Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!

After some mathematical rewrite, turns out all of transformer is a series of gemm + epilogue. Given a few optimized primitives, LLMs (and novice humans) can write speed-of-light kernels for all transformer ops!








@stochasticchasm @thsottiaux ok i fixed it. symlinked codex and node into ~/.local/bin i think the correct fix is either 1) make codex app use a login shell ie /bin/sh -lc so it gets my .profile 2) make codex app prepend more common .nvm paths to the hardcoded search paths











