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← A lab should spend most of its compute on research rather than on…

17 connected korrents · 16 moments on record from 28 Jul 2023 to 4 Sept 2026.

Everything filed under scaling laws scaling laws Everything filed under AI agents AI agents Everything filed under AI and science AI and science Everything filed under Google Google Everything filed under benchmarks benchmarks Everything filed under reinforcement learning reinforcement learning Everything filed under coding agents coding agents Same subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subject Read this korrent: 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. A lab should spend most of its compute onresearch rather than on building the nextmodel, because research is where thetenfold yearly efficiency gains come from. Last stated 6 months ago 13 Mar 2026 DP Dylan Patel — holds since 2026-03-13 — 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 2 months ago 26 Jun 2026 NB Noam Brown — holds since 2026-06-26 — tap for who they are Same subject: After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute. — tap to centre the map on it After pre-training, post-trainingand test-time scaling, the fourthscaling law is agentic: multiplyingAI by spawning agents, and the wholeloop scales on one thing, compute. Last stated 6 months ago 23 Mar 2026 JH Jensen Huang — holds since 2026-03-23 — tap for who they are Same subject: Bet on a system that is maximally learned and minimally constrained, and add structure only where it improves the scaling laws. — tap to centre the map on it Bet on a system that is maximallylearned and minimally constrained,and add structure only where itimproves the scaling laws. Last stated a month ago 3 Aug 2026 DD Dmitri Dolgov — holds since 2026-08-03 — tap for who they are Same subject: Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency. — tap to centre the map on it Current AI techniques are four tosix orders of magnitude away fromoptimal in data efficiency andtest-time compute efficiency. Last stated a month ago 7 Aug 2026 FC François Chollet — holds since 2026-08-07 — tap for who they are Same subject: Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared. — tap to centre the map on it Large language models could stillplateau, and that possibility shouldbe held open even though no evidenceof it has appeared. Last stated 2 weeks ago 26 Aug 2026 DH David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are Same subject: Model comparisons understate real progress, because benchmark tables do not control for how much test-time compute each answer used. — tap to centre the map on it Model comparisons understate realprogress, because benchmark tablesdo not control for how muchtest-time compute each answer used. Last stated 2 months ago 26 Jun 2026 NB Noam Brown — holds since 2026-06-26 — 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 9 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 4 weeks ago 12 Aug 2026 CF Chelsea Finn — holds since 2026-08-12 — tap for who they are Same subject: Auto-mode does not yet convincingly fix prompt-injection risk for coding agents. — tap to centre the map on it Auto-mode does not yet convincinglyfix prompt-injection risk for codingagents. Last stated a month ago 8 Aug 2026 SW Simon Willison — holds since 2026-08-08 — tap for who they are Same subject: Current prompt-injection defenses for AI agents (such as auto mode) are now reliable enough that agents can practically be assumed safe from successful injection attacks. — tap to centre the map on it Current prompt-injection defensesfor AI agents (such as auto mode)are now reliable enough that agentscan practically be assumed safe fromsuccessful injection attacks. Last stated 4 days ago 4 Sept 2026 ZM Zvi Mowshowitz — holds since 2026-09-04 — tap for who they are Same subject: Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject. — tap to centre the map on it Do not run a personal agent on acheap or local model: weak modelsare gullible and easy toprompt-inject. Last stated 7 months ago 12 Feb 2026 PS Peter Steinberger — holds since 2026-02-12 — tap for who they are Same subject: A crewed rocket cannot be made safe by making the booster reliable, so the only real way to improve safety is to carry an escape system. — tap to centre the map on it A crewed rocket cannot be made safeby making the booster reliable, sothe only real way to improve safetyis to carry an escape system. Last stated 3 years ago 14 Dec 2023 JB Jeff Bezos — holds since 2023-12-14 — tap for who they are Same subject: A monopolist that can no longer grow by winning new users can only grow by making its product worse for the users it already has. — tap to centre the map on it A monopolist that can no longer growby winning new users can only growby making its product worse for theusers it already has. Last stated 3 years ago 28 Jul 2023 CD Cory Doctorow — holds since 2023-07-28 — tap for who they are Same subject: A startup does not have to set out to build the greatest business in history; a merely good business is a legitimate thing to aim at. — tap to centre the map on it A startup does not have to set outto build the greatest business inhistory; a merely good business is alegitimate thing to aim at. Last stated 2 years ago 19 Jun 2024 AS Aravind Srinivas — holds since 2024-06-19 — tap for who they are Same subject: AI could compete with human mathematicians once it acquires a mathematical sense of smell: knowing which way of splitting a problem makes it easier rather than harder. — tap to centre the map on it AI could compete with humanmathematicians once it acquires amathematical sense of smell: knowingwhich way of splitting a problemmakes it easier rather than harder. Last stated a year ago 14 Jun 2025 TT Terence Tao — holds since 2025-06-14 — tap for who they are Same subject: AI in chess and mathematics does not explain anything; it says which position is better, and humans build the theory from that. — tap to centre the map on it AI in chess and mathematics does notexplain anything; it says whichposition is better, and humans buildthe theory from that. Last stated a year ago 14 Jun 2025 LF Lex Fridman — holds since 2025-06-14 — tap for who they are Same subject: AI will transform how scientific discovery is done, and within two or three years a working scientist's job will already look dramatically different. — tap to centre the map on it AI will transform how scientificdiscovery is done, and within two orthree years a working scientist'sjob will already look dramaticallydifferent. Last stated 3 weeks ago 18 Aug 2026 MK Michael Kratsios — holds since 2026-08-18 — tap for who they are
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At the centre 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. Last stated 13 Mar 2026 · 6 months ago Holds Dylan Patel Read this korrent →