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← You cannot build an AI that has only the capabilities you want,…
17 connected korrents · 17 moments from 10 Jun 2022 to 15 Sept 2026.
Everything filed under AI alignment
AI alignment
Everything filed under AGI
AGI
Everything filed under AI agents
AI agents
Everything filed under reinforcement learning
reinforcement learning
Everything filed under optimizers
optimizers
Everything filed under vibe coding
vibe coding
Everything filed under LLMs
LLMs
Everything filed under curiosity
curiosity
Everything filed under mathematics
mathematics
Everything filed under code generation
code generation 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: You cannot build an AI that has only the capabilities you want, because the algorithms that solve the problems you want generalize to the ones you do not. You cannot build an AI that has only the capabilities you want, because the algorithms that solve the problems you want generalize to the ones you do not. Last stated 4 years ago
10 Jun 2022
EY
Eliezer Yudkowsky — holds since 2022-06-10 — tap for who they are
Same subject: Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well. — tap to centre the map on it Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well. Last stated a year ago
26 Sept 2025
RS
Richard Sutton — holds since 2025-09-26 — tap for who they are
Same subject: The hard question is no longer how to build something but what to build, because anything already described can be replicated. — tap to centre the map on it The hard question is no longer how to build something but what to build, because anything already described can be replicated. Last stated 7 months ago
29 Mar 2026
CH
Chip Huyen — holds since 2026-03-29 — tap for who they are
Same subject: AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away. — tap to centre the map on it AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away. Last stated 2 months ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — tap for who they are
Same subject: A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it. — tap to centre the map on it A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it. Last stated 4 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: AI works best when it solves a specific problem for a particular community rather than trying to be all things to all people. — tap to centre the map on it AI works best when it solves a specific problem for a particular community rather than trying to be all things to all people. Last stated 6 months ago
28 Apr 2026
AD
Anil Dash — holds since 2026-04-28 — tap for who they are
Same subject: People often seem to focus on what AI can execute and not on what it can teach them. — tap to centre the map on it People often seem to focus on what AI can execute and not on what it can teach them. Last stated a month ago
10 Sept 2026
KS
Karri Saarinen — holds since 2026-09-10 — tap for who they are
Same subject: What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. — tap to centre the map on it What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. Last stated 7 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: AI is still at its best when it can reuse great components rather than regenerating them every time from first principles. — tap to centre the map on it AI is still at its best when it can reuse great components rather than regenerating them every time from first principles. Last stated a month ago
8 Sept 2026
GR
Guillermo Rauch — holds since 2026-09-08 — 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 5 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — 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 model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality — tap to centre the map on it A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality Last stated 3 years ago
10 Oct 2023
CH
Chip Huyen — holds since 2023-10-10 — 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 3 months 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 11 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 3 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does. — tap to centre the map on it A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does. Last stated 5 months ago
21 May 2026
RK
Rohit Krishnan — holds since 2026-05-21 — tap for who they are
Same subject: A company cannot be led by machines, because nobody would have recourse against them. — tap to centre the map on it A company cannot be led by machines, because nobody would have recourse against them. Last stated a month ago
15 Sept 2026
TL
Tobias Lütke — holds since 2026-09-15 — tap for who they are
Same subject: A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor. — tap to centre the map on it A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor. Last stated 2 months ago
10 Aug 2026
PS
Peter Steinberger — holds since 2026-08-10 — tap for who they are
At the centre
You cannot build an AI that has only the capabilities you want, because the algorithms that solve the problems you want generalize to the ones you do not.
Holds Read this korrent →
Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well.
Holds
The hard question is no longer how to build something but what to build, because anything already described can be replicated.
Holds
AI systems keep trying hard outside training because a model that only exerted itself when it detected training would be useless and would be selected away.
Holds
A model can make an existing algorithm a hundred times faster and still cannot invent a better one, however long you give it.
Holds
AI works best when it solves a specific problem for a particular community rather than trying to be all things to all people.
Holds
People often seem to focus on what AI can execute and not on what it can teach them.
Holds
What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use.
Holds
AI is still at its best when it can reuse great components rather than regenerating them every time from first principles.
Holds
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
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
A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds
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
A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does.
Holds
A company cannot be led by machines, because nobody would have recourse against them.
Holds
A computer-using agent needs a machine of its own, or you will spend the day fighting it for the mouse cursor.
Holds