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← The test of a scientific model is not whether supporting evidence can…
17 connected korrents · 16 moments on record from 12 Feb 2010 to 4 Sept 2026.
Everything filed under scaling laws
scaling laws
Everything filed under taste
taste
Everything filed under reinforcement learning
reinforcement learning
Everything filed under LLMs
LLMs
Everything filed under mathematics
mathematics
Everything filed under design
design Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: The test of a scientific model is not whether supporting evidence can be found for it, but whether it fits the totality of the evidence. The test of a scientific model is not whether supporting evidence can be found for it, but whether it fits the totality of the evidence. Last stated 8 years ago
3 Jul 2018
SG
Stephan Guyenet — holds since 2018-07-03 — tap for who they are
Same subject: The hypotheses AI 'co-scientist' systems are producing are ones the literature already contains, and the publicity around them does not say so. — tap to centre the map on it The hypotheses AI 'co-scientist' systems are producing are ones the literature already contains, and the publicity around them does not say so. Last stated 3 months ago
27 May 2026
DL
Derek Lowe — holds since 2026-05-27 — tap for who they are
Same subject: "There is no empirical evidence against my position" is not an argument for it. — tap to centre the map on it "There is no empirical evidence against my position" is not an argument for it. Last stated 12 years ago
7 Nov 2014
DL
Dan Luu — holds since 2014-11-07 — tap for who they are
Same subject: Models have no research taste yet, which is why they complement researchers rather than replace them. — tap to centre the map on it Models have no research taste yet, which is why they complement researchers rather than replace them. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: 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. — tap to centre the map on it 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 3 days ago
4 Sept 2026
FL
Fei-Fei Li — holds since 2026-09-04 — tap for who they are
Same subject: Models can prove monumental theorems and still have never written an essay worth reading. — tap to centre the map on it Models can prove monumental theorems and still have never written an essay worth reading. Last stated a month ago
31 Jul 2026
PC
Patrick Collison — holds since 2026-07-31 — tap for who they are
Same subject: The twin prime conjecture is certainly true, the random model gives overwhelming odds of it, and he just cannot prove it. — tap to centre the map on it The twin prime conjecture is certainly true, the random model gives overwhelming odds of it, and he just cannot prove it. Last stated a year ago
14 Jun 2025
TT
Terence Tao — holds since 2025-06-14 — tap for who they are
Same subject: A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. — tap to centre the map on it A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. Last stated a month ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: The fear that a great theorem will arrive as an incomprehensible proof is misplaced, because once the proof exists as an artifact we can analyse it. — tap to centre the map on it The fear that a great theorem will arrive as an incomprehensible proof is misplaced, because once the proof exists as an artifact we can analyse it. Last stated 6 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — 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 be reported under a stated budget, or as 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: 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 its compute on research rather than on building the next model, because research is where the tenfold 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: 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-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. Last stated 6 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: A first draft should not be graded good or bad; it is only the material that taste then gets to act on. — tap to centre the map on it A first draft should not be graded good or bad; it is only the material that taste then gets to act on. Last stated a month ago
6 Aug 2026
GS
George Saunders — holds since 2026-08-06 — tap for who they are
Same subject: A lot of people can match a framework for taste; almost nobody can create one, and creating one is the rare skill. — tap to centre the map on it A lot of people can match a framework for taste; almost nobody can create one, and creating one is the rare skill. Last stated 11 months ago
16 Oct 2025
DF
Dylan Field — holds since 2025-10-16 — tap for who they are
Same subject: A product needs a soul, and for that it needs one person of great taste who is its living, breathing aspect and gets furious about every small detail. — tap to centre the map on it A product needs a soul, and for that it needs one person of great taste who is its living, breathing aspect and gets furious about every small detail. Last stated 17 years ago
12 Feb 2010
KS
Karri Saarinen — holds since 2010-02-12 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. — tap to centre the map on it Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. Last stated 6 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. — tap to centre the map on it Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
At the centre
The test of a scientific model is not whether supporting evidence can be found for it, but whether it fits the totality of the evidence.
Holds SG Stephan GuyenetRead this korrent →
The hypotheses AI 'co-scientist' systems are producing are ones the literature already contains, and the publicity around them does not say so.
Holds DL Derek Lowe
"There is no empirical evidence against my position" is not an argument for it.
Holds DL Dan Luu
Models have no research taste yet, which is why they complement researchers rather than replace them.
Holds NB Noam Brown
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.
Holds FL Fei-Fei Li
Models can prove monumental theorems and still have never written an essay worth reading.
Holds
The twin prime conjecture is certainly true, the random model gives overwhelming odds of it, and he just cannot prove it.
Holds TT Terence Tao
A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next.
Holds JD Jeff Dean
The fear that a great theorem will arrive as an incomprehensible proof is misplaced, because once the proof exists as an artifact we can analyse it.
Holds TT Terence Tao
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds NB Noam Brown
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.
Holds DP Dylan Patel
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.
Holds JH Jensen Huang
A first draft should not be graded good or bad; it is only the material that taste then gets to act on.
Holds GS George Saunders
A lot of people can match a framework for taste; almost nobody can create one, and creating one is the rare skill.
Holds DF Dylan Field
A product needs a soul, and for that it needs one person of great taste who is its living, breathing aspect and gets furious about every small detail.
Holds KS Karri Saarinen
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago.
Holds
Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving.
Holds