This started with Addition Under Pressure, where I gave Claude Code and Codex the same prompt: train the smallest possible transformer that can do 10-digit addition with at least 99% accuracy. Claude Code came back with 6,080 parameters and Codex came back with 1,644. The community has since pushed this dramatically lower.
But those tricks, I believe, are quite clear to everybody that has worked extensively with automatic programming in the latest months. To think in terms of “what a human would need” is often the best bet, plus a few LLMs specific things, like the forgetting issue after context compaction, the continuous ability to verify it is on the right track, and so forth.
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this iteration.
В офисе Зеленского описали одну ключевую меру по урегулированию конфликтаКислица: Необходимо четко обозначить термин «гарантия безопасности»