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← Humans collapse over the course of a life exactly as models do;…
17 connected korrents · 16 moments on record from 19 Aug 2020 to 20 Aug 2026.
Everything filed under LLMs
LLMs
Everything filed under scaling laws
scaling laws
Everything filed under reinforcement learning
reinforcement learning
Everything filed under demographics
demographics 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: Humans collapse over the course of a life exactly as models do; children say shocking things because they have not overfitted yet. Humans collapse over the course of a life exactly as models do; children say shocking things because they have not overfitted yet. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: There is no human analogue to pre-training — neither childhood nor evolution is the same thing as it. — tap to centre the map on it There is no human analogue to pre-training — neither childhood nor evolution is the same thing as it. Last stated 9 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A model may have a worldview of its own, but it can never be placed above a person under any circumstance. — tap to centre the map on it A model may have a worldview of its own, but it can never be placed above a person under any circumstance. Last stated 3 months ago
3 Jun 2026
KH
Kelsey Hightower — holds since 2026-06-03 — tap for who they are
Same subject: Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. — tap to centre the map on it Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. Last stated 11 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: The accepted model of how archaic and modern humans relate has been accreted and patched rather than built, and is due for a simpler replacement. — tap to centre the map on it The accepted model of how archaic and modern humans relate has been accreted and patched rather than built, and is due for a simpler replacement. Last stated 4 months ago
8 May 2026
DR
David Reich — holds since 2026-05-08 — tap for who they are
Same subject: A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world. — tap to centre the map on it A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world. Last stated 11 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: Every age of life is less deadly than it was for the generation before, not just childhood. — tap to centre the map on it Every age of life is less deadly than it was for the generation before, not just childhood. Last stated 3 years ago
2 Jan 2024
SD
Saloni Dattani — holds since 2024-01-02 — tap for who they are
Same subject: Societies rarely recognise their own collapse while it is happening: Roman and Mayan thinkers left almost no reflection on theirs. — tap to centre the map on it Societies rarely recognise their own collapse while it is happening: Roman and Mayan thinkers left almost no reflection on theirs. Last stated 6 years ago
19 Aug 2020
SB
Samo Burja — holds since 2020-08-19 — tap for who they are
Same subject: Calling the fall in birth rates a mystery is not humility but obscurantism: there is already a good causal account of it. — tap to centre the map on it Calling the fall in birth rates a mystery is not humility but obscurantism: there is already a good causal account of it. Last stated 3 weeks ago
20 Aug 2026
LS
Lyman Stone — holds since 2026-08-20 — tap for who they are
Same subject: A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. — tap to centre the map on it A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: A language model is not using language at all, because language requires an intention to communicate. — tap to centre the map on it A language model is not using language at all, because language requires an intention to communicate. Last stated 2 years ago
31 Aug 2024
TC
Ted Chiang — holds since 2024-08-31 — tap for who they are
Same subject: A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. — tap to centre the map on it A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human. Last stated 2 years ago
22 Apr 2024
SC
Sean Carroll — holds since 2024-04-22 — 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 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
Humans collapse over the course of a life exactly as models do; children say shocking things because they have not overfitted yet.
Holds Read this korrent →
There is no human analogue to pre-training — neither childhood nor evolution is the same thing as it.
Holds IS Ilya Sutskever
A model may have a worldview of its own, but it can never be placed above a person under any circumstance.
Holds KH Kelsey Hightower
Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew.
Holds RS Richard Sutton
The accepted model of how archaic and modern humans relate has been accreted and patched rather than built, and is due for a simpler replacement.
Holds DR David Reich
A language model can predict what a person would say but not what will happen, and only the second of those is a model of the world.
Holds RS Richard Sutton
Every age of life is less deadly than it was for the generation before, not just childhood.
Holds SD Saloni Dattani
Societies rarely recognise their own collapse while it is happening: Roman and Mayan thinkers left almost no reflection on theirs.
Holds SB Samo Burja
Calling the fall in birth rates a mystery is not humility but obscurantism: there is already a good causal account of it.
Holds LS Lyman Stone
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Holds GM Gary Marcus
A language model is not using language at all, because language requires an intention to communicate.
Holds TC Ted Chiang
A language model's apparent mind is mostly our own bias: it predicts text, and leverages our evolved habit of attributing intentionality to anything that acts human.
Holds SC Sean Carroll
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 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