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← Reason is only one of several evolved mental faculties, and treating…
17 connected korrents · 13 moments on record from 24 Feb 2018 to 10 Aug 2026.
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robotics 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: Reason is only one of several evolved mental faculties, and treating it as the gold standard misdescribes how people decide. Reason is only one of several evolved mental faculties, and treating it as the gold standard misdescribes how people decide. Last stated 9 months ago
9 Dec 2025
RS
Rory Sutherland — holds since 2025-12-09 — tap for who they are
Same subject: Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all. — tap to centre the map on it Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: Humanity's advantage is accumulated shared knowledge rather than higher intelligence — and AI models, which vanish with their context window, have none of it. — tap to centre the map on it Humanity's advantage is accumulated shared knowledge rather than higher intelligence — and AI models, which vanish with their context window, have none of it. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: The gap between chimps and humans is no evidence that a small increase in compute yields an explosion of capability, because evolution was not optimising chimps for technology. — tap to centre the map on it The gap between chimps and humans is no evidence that a small increase in compute yields an explosion of capability, because evolution was not optimising chimps for technology. Last stated 9 years ago
24 Feb 2018
PC
Paul Christiano — holds since 2018-02-24 — tap for who they are
Same subject: A new technology is judged against perfection rather than against the thing it would replace, which is why it always comes up short. — tap to centre the map on it A new technology is judged against perfection rather than against the thing it would replace, which is why it always comes up short. Last stated 2 months ago
20 Jul 2026
PB
Paul Bloom — holds since 2026-07-20 — tap for who they are
Same subject: People cannot choose without comparison, so an AI that hands over one perfect answer will not satisfy them. — tap to centre the map on it People cannot choose without comparison, so an AI that hands over one perfect answer will not satisfy them. Last stated 9 months ago
9 Dec 2025
RS
Rory Sutherland — holds since 2025-12-09 — tap for who they are
Same subject: Group theory took a hundred years to travel from one man's hunch to something the mathematical community agreed was good, passing through many heads on the way. — tap to centre the map on it Group theory took a hundred years to travel from one man's hunch to something the mathematical community agreed was good, passing through many heads on the way. Last stated 2 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: The moral theory underneath longtermism treats people as containers of value rather than as the point of it, which is why creating more of them counts as making the universe better. — tap to centre the map on it The moral theory underneath longtermism treats people as containers of value rather than as the point of it, which is why creating more of them counts as making the universe better. Last stated 5 years ago
19 Oct 2021
ÉT
Émile P. Torres — holds since 2021-10-19 — tap for who they are
Same subject: The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds. — tap to centre the map on it The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds. Last stated 2 years ago
3 Feb 2025
DP
Dylan Patel — holds since 2025-02-03 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 2 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. — tap to centre the map on it A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. Last stated 4 weeks ago
10 Aug 2026
FL
Fei-Fei Li — holds since 2026-08-10 — tap for who they are
Same subject: A frontier model is measurably more intelligent with no system prompt at all; the prompts that remain are there for the product, not the model. — tap to centre the map on it A frontier model is measurably more intelligent with no system prompt at all; the prompts that remain are there for the product, not the model. Last stated a month ago
27 Jul 2026
BC
Boris Cherny — holds since 2026-07-27 — tap for who they are
Same subject: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. — tap to centre the map on it A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — 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: Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. — tap to centre the map on it Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — 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: 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 a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
At the centre
Reason is only one of several evolved mental faculties, and treating it as the gold standard misdescribes how people decide.
Holds RS Rory SutherlandRead this korrent →
Reasoning is not taught to a model by people: it emerges from reinforcement learning on questions with checkable answers, with no human preference data at all.
Holds NL Nathan Lambert
Humanity's advantage is accumulated shared knowledge rather than higher intelligence — and AI models, which vanish with their context window, have none of it.
Holds NB Noam Brown
The gap between chimps and humans is no evidence that a small increase in compute yields an explosion of capability, because evolution was not optimising chimps for technology.
Holds PC Paul Christiano
A new technology is judged against perfection rather than against the thing it would replace, which is why it always comes up short.
Holds PB Paul Bloom
People cannot choose without comparison, so an AI that hands over one perfect answer will not satisfy them.
Holds RS Rory Sutherland
Group theory took a hundred years to travel from one man's hunch to something the mathematical community agreed was good, passing through many heads on the way.
Holds GS Grant Sanderson
The moral theory underneath longtermism treats people as containers of value rather than as the point of it, which is why creating more of them counts as making the universe better.
Holds ÉT Émile P. Torres
The aha moment for reasoning models will come from computer use and robotics rather than from scientific discovery, because those are the infinitely verifiable playgrounds.
Holds DP Dylan Patel
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds DH Dex Horthy
A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved.
Holds FL Fei-Fei Li
A frontier model is measurably more intelligent with no system prompt at all; the prompts that remain are there for the product, not the model.
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds DD Dmitri Dolgov
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model.
Holds DD Dmitri Dolgov
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
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.
Holds NB Noam Brown