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← Good scientists can be shortlisted from their publication record,…
17 connected korrents · 16 moments on record from 8 Jan 2021 to 26 Aug 2026.
Everything filed under reinforcement learning
reinforcement learning
Everything filed under robotics
robotics
Everything filed under scaling laws
scaling laws
Everything filed under peer review
peer review
Everything filed under taste
taste
Everything filed under LLMs
LLMs 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: Good scientists can be shortlisted from their publication record, leaving human reviewers only the job of choosing among them. Good scientists can be shortlisted from their publication record, leaving human reviewers only the job of choosing among them. Last stated 6 years ago
8 Jan 2021
JR
José Luis Ricón — holds since 2021-01-08 — tap for who they are
Same subject: Humans keep their place in AI as judges rather than authors, because telling which of two answers is better is far easier than writing a good one. — tap to centre the map on it Humans keep their place in AI as judges rather than authors, because telling which of two answers is better is far easier than writing a good one. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: Peer reviewers miss most of the serious errors in the papers they review. — tap to centre the map on it Peer reviewers miss most of the serious errors in the papers they review. Last stated 4 years ago
13 Dec 2022
AM
Adam Mastroianni — holds since 2022-12-13 — 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: Gatekeeping in science stamps out the best research along with the worst, because reviewers are least likely to approve what is novel or risky. — tap to centre the map on it Gatekeeping in science stamps out the best research along with the worst, because reviewers are least likely to approve what is novel or risky. Last stated 3 years ago
11 Apr 2023
AM
Adam Mastroianni — holds since 2023-04-11 — tap for who they are
Same subject: The demands of peer reviewers push scientists into producing bad research. — tap to centre the map on it The demands of peer reviewers push scientists into producing bad research. Last stated 4 years ago
13 Dec 2022
AM
Adam Mastroianni — holds since 2022-12-13 — tap for who they are
Same subject: Work produced by one frontier model should be reviewed by a different one, for the same reason a good programmer's work improves under a good peer's review. — tap to centre the map on it Work produced by one frontier model should be reviewed by a different one, for the same reason a good programmer's work improves under a good peer's review. Last stated 2 weeks ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are
Same subject: Reference checks are more informative than interviews, and if you had to pick one you should pick references. — tap to centre the map on it Reference checks are more informative than interviews, and if you had to pick one you should pick references. Last stated 2 years ago
17 Dec 2024
CM
Charity Majors — holds since 2024-12-17 — tap for who they are
Same subject: Pre-grant peer review predicts which research will have impact substantially better than chance does. — tap to centre the map on it Pre-grant peer review predicts which research will have impact substantially better than chance does. Last stated 6 years ago
20 Jan 2021
JR
José Luis Ricón — holds since 2021-01-20 — 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
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 highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. — tap to centre the map on it A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. Last stated 3 years ago
1 Oct 2023
TC
Tyler Cowen — holds since 2023-10-01 — tap for who they are
Same subject: A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. — tap to centre the map on it A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. Last stated a year ago
6 Apr 2025
MH
Molson Hart — holds since 2025-04-06 — tap for who they are
Same subject: A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. — tap to centre the map on it A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
At the centre
Good scientists can be shortlisted from their publication record, leaving human reviewers only the job of choosing among them.
Holds JR José Luis RicónRead this korrent →
Humans keep their place in AI as judges rather than authors, because telling which of two answers is better is far easier than writing a good one.
Holds NL Nathan Lambert
Peer reviewers miss most of the serious errors in the papers they review.
Holds AM Adam Mastroianni
Models have no research taste yet, which is why they complement researchers rather than replace them.
Holds NB Noam Brown
Gatekeeping in science stamps out the best research along with the worst, because reviewers are least likely to approve what is novel or risky.
Holds AM Adam Mastroianni
The demands of peer reviewers push scientists into producing bad research.
Holds AM Adam Mastroianni
Work produced by one frontier model should be reviewed by a different one, for the same reason a good programmer's work improves under a good peer's review.
Holds
Reference checks are more informative than interviews, and if you had to pick one you should pick references.
Holds CM Charity Majors
Pre-grant peer review predicts which research will have impact substantially better than chance does.
Holds JR José Luis Ricón
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
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 highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas.
Holds TC Tyler Cowen
A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it.
Holds MH Molson Hart
A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases.
Holds DD Dmitri Dolgov