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← The scaling law for world models was a conviction held in advance, not…

17 connected korrents · 13 moments from 11 Oct 2018 to 4 Sept 2026. Nearly all of them are about world models.

Everything filed under scaling laws scaling laws Everything filed under recursive self-improvement recursive self-improvement Everything filed under AGI AGI Everything filed under startups startups Same subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subject Read this korrent: The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. The scaling law for world models was aconviction held in advance, not adiscovery; the devils were always in thearchitecture choices and the data mixture. Last stated 2 months ago 4 Sept 2026 FL Fei-Fei Li — holds since 2026-09-04 — tap for who they are Same subject: An adaptive agent's world model cannot be a static representation learned once and fixed — tap to centre the map on it An adaptive agent's world modelcannot be a static representationlearned once and fixed Last stated a year ago 17 Jul 2025 FC François Chollet — holds since 2025-07-17 — tap for who they are Same subject: Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop. — tap to centre the map on it Coding is not just anotherapplication domain for AI; it is themeta-skill that lets AI generate itsown training material and start therecursive self-improvement loop. Last stated 2 months ago 10 Aug 2026 FC François Chollet — holds since 2026-08-10 — tap for who they are Same subject: Current AI evaluation of world models is too narrow, favoring static representations learned from massive datasets over efficient learning through interaction — tap to centre the map on it Current AI evaluation of worldmodels is too narrow, favoringstatic representations learned frommassive datasets over efficientlearning through interaction Last stated a year ago 17 Jul 2025 FC François Chollet — holds since 2025-07-17 — tap for who they are Same subject: Games are particularly rich and controlled environments uniquely well-suited for evaluating rapid world model induction in AI — tap to centre the map on it Games are particularly rich andcontrolled environments uniquelywell-suited for evaluating rapidworld model induction in AI Last stated a year ago 17 Jul 2025 FC François Chollet — holds since 2025-07-17 — tap for who they are Same subject: Human adaptability is fundamentally linked to the efficient construction and refinement of internal world models — tap to centre the map on it Human adaptability is fundamentallylinked to the efficient constructionand refinement of internal worldmodels Last stated a year ago 17 Jul 2025 FC François Chollet — holds since 2025-07-17 — tap for who they are Same subject: Rapid world model induction will be critical for achieving robust, general AI that functions in complex, fast-changing real and human worlds — tap to centre the map on it Rapid world model induction will becritical for achieving robust,general AI that functions incomplex, fast-changing real andhuman worlds Last stated a year ago 17 Jul 2025 FC François Chollet — holds since 2025-07-17 — tap for who they are Same subject: The companies that already control the largest troves of real-world video data will be first to build successful world models. — tap to centre the map on it The companies that already controlthe largest troves of real-worldvideo data will be first to buildsuccessful world models. Last stated 2 months ago 10 Aug 2026 KK Kevin Kelly — holds since 2026-08-10 — tap for who they are Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should bereported under a stated budget, oras a curve against test-time compute— never as a single number. Last stated 4 months ago 26 Jun 2026 NB Noam Brown — holds since 2026-06-26 — tap for who they are Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because itwas one word: naming a researchdirection is what tells a wholefield what to do next. Last stated 11 months ago 25 Nov 2025 IS Ilya Sutskever — holds since 2025-11-25 — tap for who they are Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of itscompute on research rather than onbuilding the next model, becauseresearch is where the tenfold yearlyefficiency gains come from. Last stated 7 months ago 13 Mar 2026 DP Dylan Patel — holds since 2026-03-13 — tap for who they are Same subject: A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. — tap to centre the map on it A model's capability is now afunction of how much money you spendon it, so asking what a model can domeans nothing until you name abudget. Last stated 4 months ago 26 Jun 2026 NB Noam Brown — holds since 2026-06-26 — tap for who they are Same subject: AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard. — tap to centre the map on it AI progress is faster than peopleexpect, and ordinary scaling can beenough to solve problems that lookedvery hard. Last stated 2 years ago 2 Feb 2025 AC Ajeya Cotra — holds since 2023-08-29 — tap for who they are SA Scott Alexander — holds since 2022-09-12 — tap for who they are MB Miles Brundage — holds since 2025-02-02 — tap for who they are Same subject: As models keep growing, AI is running out of enough high-quality unique training tokens to keep up. — tap to centre the map on it As models keep growing, AI isrunning out of enough high-qualityunique training tokens to keep up. Last stated 4 months ago 24 Jun 2026 LW Lilian Weng — holds since 2026-06-24 — tap for who they are Same subject: Current techniques restrict pre-trained representation power because standard language models are unidirectional. — tap to centre the map on it Current techniques restrictpre-trained representation powerbecause standard language models areunidirectional. Last stated 8 years ago 11 Oct 2018 KT Kristina Toutanova — holds since 2018-10-11 — tap for who they are MC Ming-Wei Chang — holds since 2018-10-11 — tap for who they are KL Kenton Lee — holds since 2018-10-11 — tap for who they are JD Jacob Devlin — holds since 2018-10-11 — tap for who they are Same subject: Models resemble each other because pre-training is the same everywhere; what differentiates labs now is RL and post-training. — tap to centre the map on it Models resemble each other becausepre-training is the same everywhere;what differentiates labs now is RLand post-training. Last stated 11 months ago 25 Nov 2025 IS Ilya Sutskever — holds since 2025-11-25 — tap for who they are Same subject: One pre-trained robot model now matches or beats the specialists that were fine-tuned with reinforcement learning for the very tasks they were built for. — tap to centre the map on it One pre-trained robot model nowmatches or beats the specialiststhat were fine-tuned withreinforcement learning for the verytasks they were built for. Last stated 2 months ago 12 Aug 2026 CF Chelsea Finn — holds since 2026-08-12 — tap for who they are Same subject: Pre-training is a crappy evolution: the practically buildable substitute for the process that gave animals their built-in hardware. — tap to centre the map on it Pre-training is a crappy evolution:the practically buildable substitutefor the process that gave animalstheir built-in hardware. Last stated a year ago 17 Oct 2025 AK Andrej Karpathy — holds since 2025-10-17 — tap for who they are
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At the centre The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. Last stated 4 Sept 2026 · 2 months ago Holds Fei-Fei Li Read this korrent →