Tap a claim on the ring to put it at the centre.
← Computer-use agents had to wait for language models: without…
17 connected korrents · 13 moments on record from 21 Jan 2019 to 26 Aug 2026.
Everything filed under robotics
robotics
Everything filed under AGI
AGI
Everything filed under formal proof
formal proof
Everything filed under LLMs
LLMs
Everything filed under AI agents
AI agents
Everything filed under scaling laws
scaling laws
Everything filed under reinforcement learning
reinforcement learning 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: Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from. Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. — tap to centre the map on it Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: The scarce skill is now context switching across parallel agents, not sustained deep work. — tap to centre the map on it The scarce skill is now context switching across parallel agents, not sustained deep work. Last stated 6 months ago
4 Mar 2026
BC
Boris Cherny — holds since 2026-03-04 — tap for who they are
Same subject: The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. — tap to centre the map on it The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Large language models start in exactly the wrong place, because they try to get by without a goal and therefore without any sense of better or worse. — tap to centre the map on it Large language models start in exactly the wrong place, because they try to get by without a goal and therefore without any sense of better or worse. Last stated 11 months ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: Agents will take a decade rather than a year, because today's models are cognitively lacking in too many independent ways at once. — tap to centre the map on it Agents will take a decade rather than a year, because today's models are cognitively lacking in too many independent ways at once. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — 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: 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: 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 still plateau, and that possibility should be held open even though no evidence of 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: Formalising a proof in Lean currently takes about ten times the effort of writing it out: doable, but annoying. — tap to centre the map on it Formalising a proof in Lean currently takes about ten times the effort of writing it out: doable, but annoying. Last stated a year ago
14 Jun 2025
TT
Terence Tao — holds since 2025-06-14 — tap for who they are
Same subject: Full formal verification is a waste of money for most software: near-perfect is reachable with ordinary techniques at a fraction of the cost. — tap to centre the map on it Full formal verification is a waste of money for most software: near-perfect is reachable with ordinary techniques at a fraction of the cost. Last stated 8 years ago
21 Jan 2019
HW
Hillel Wayne — holds since 2019-01-21 — tap for who they are
Same subject: Lean and tools like GitHub will let experimental mathematics scale far beyond what one mathematician's spaghetti code allows today. — tap to centre the map on it Lean and tools like GitHub will let experimental mathematics scale far beyond what one mathematician's spaghetti code allows today. Last stated a year ago
14 Jun 2025
TT
Terence Tao — holds since 2025-06-14 — tap for who they are
Same subject: A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. — tap to centre the map on it A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. Last stated 3 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
Same subject: A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. — tap to centre the map on it A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean. Last stated 9 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A poor country should prioritise owning a piece of AI over retraining its workers, but it should not bet everything on that. — tap to centre the map on it A poor country should prioritise owning a piece of AI over retraining its workers, but it should not bet everything on that. Last stated 3 months ago
4 Jun 2026
PT
Phil Trammell — holds since 2026-06-04 — 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
Computer-use agents had to wait for language models: without pre-trained representations the reward is too sparse to ever learn from.
Holds Read this korrent →
Reinforcement learning cannot be scaled for robots the way it was for language models, because every attempt spends real robot hours instead of data-centre compute.
Holds CF Chelsea Finn
The scarce skill is now context switching across parallel agents, not sustained deep work.
Holds
The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out.
Holds
Large language models start in exactly the wrong place, because they try to get by without a goal and therefore without any sense of better or worse.
Holds RS Richard Sutton
Agents will take a decade rather than a year, because today's models are cognitively lacking in too many independent ways at once.
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
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
Large language models could still plateau, and that possibility should be held open even though no evidence of it has appeared.
Holds
Formalising a proof in Lean currently takes about ten times the effort of writing it out: doable, but annoying.
Holds TT Terence Tao
Full formal verification is a waste of money for most software: near-perfect is reachable with ordinary techniques at a fraction of the cost.
Holds HW Hillel Wayne
Lean and tools like GitHub will let experimental mathematics scale far beyond what one mathematician's spaghetti code allows today.
Holds TT Terence Tao
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Holds AI Alex Imas
A human being is not an AGI: we lack a huge amount of knowledge and rely on continual learning instead, so continual learning is what superintelligence should mean.
Holds IS Ilya Sutskever
A poor country should prioritise owning a piece of AI over retraining its workers, but it should not bet everything on that.
Holds PT Phil Trammell
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