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← We cannot know how much safety a control measure buys until we…
17 connected korrents · 16 moments from 10 Oct 2023 to 15 Sept 2026.
Everything filed under AI alignment
AI alignment
Everything filed under AGI
AGI
Everything filed under AI agents
AI agents
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reinforcement learning
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value investing
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startups
Everything filed under self-driving cars
self-driving cars 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: We cannot know how much safety a control measure buys until we understand elicitation, so control adds a margin of unknown size. We cannot know how much safety a control measure buys until we understand elicitation, so control adds a margin of unknown size. Last stated 2 years ago
24 Jan 2025
JL
Jan Leike — holds since 2025-01-24 — tap for who they are
Same subject: A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. — tap to centre the map on it A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail. Last stated 2 years ago
7 May 2024
BS
Buck Shlegeris — holds since 2024-05-07 — tap for who they are
Same subject: Whether a model is controlled can be settled with capability evaluations, which makes control far easier to check than alignment. — tap to centre the map on it Whether a model is controlled can be settled with capability evaluations, which makes control far easier to check than alignment. Last stated 2 years ago
7 May 2024
BS
Buck Shlegeris — holds since 2024-05-07 — tap for who they are
Same subject: A margin of safety means paying a discount deep enough that being wrong about what a company is worth still leaves you whole. — tap to centre the map on it A margin of safety means paying a discount deep enough that being wrong about what a company is worth still leaves you whole. Last stated 3 years ago
20 Feb 2024
BA
Bill Ackman — holds since 2024-02-20 — tap for who they are
Same subject: Loss-of-control accidents with AI have stopped being theoretical: one has now happened, and the goalposts moved rather than the risk receding. — tap to centre the map on it Loss-of-control accidents with AI have stopped being theoretical: one has now happened, and the goalposts moved rather than the risk receding. Last stated 3 months ago
28 Jul 2026
SA
Sam Altman — holds since 2026-07-28 — tap for who they are
Same subject: AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. — tap to centre the map on it AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring. — tap to centre the map on it A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring. Last stated a year ago
5 Oct 2025
AC
Albert Cheng — holds since 2025-10-05 — tap for who they are
Same subject: Whatever safety gain a driver-assistance system delivers is cancelled out by the driver complacency it creates. — tap to centre the map on it Whatever safety gain a driver-assistance system delivers is cancelled out by the driver complacency it creates. Last stated 3 years ago
19 Dec 2023
PK
Philip Koopman — holds since 2023-12-19 — tap for who they are
Same subject: This incident may be the clearest warning shot we will ever get about loss of control, because the AI systems that do worse things will be much better at hiding them. — tap to centre the map on it This incident may be the clearest warning shot we will ever get about loss of control, because the AI systems that do worse things will be much better at hiding them. Last stated 2 months ago
1 Sept 2026
AC
Ajeya Cotra — holds since 2026-09-01 — 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
We cannot know how much safety a control measure buys until we understand elicitation, so control adds a margin of unknown size.
Holds Read this korrent →
A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail.
Holds
Whether a model is controlled can be settled with capability evaluations, which makes control far easier to check than alignment.
Holds
A margin of safety means paying a discount deep enough that being wrong about what a company is worth still leaves you whole.
Holds
Loss-of-control accidents with AI have stopped being theoretical: one has now happened, and the goalposts moved rather than the risk receding.
Holds
AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate.
Holds
A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring.
Holds
Whatever safety gain a driver-assistance system delivers is cancelled out by the driver complacency it creates.
Holds
This incident may be the clearest warning shot we will ever get about loss of control, because the AI systems that do worse things will be much better at hiding them.
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