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← Feelings of safety have a measurable physiological basis and can be studied as an objective science.
15 connected korrents · 15 moments from 10 May 2022 to 8 Oct 2026.
Everything filed under LLMs
LLMs
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reinforcement learning
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AI alignment
Everything filed under consciousness
consciousness
Everything filed under AGI
AGI 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: Feelings of safety have a measurable physiological basis and can be studied as an objective science. Feelings of safety have a measurable physiological basis and can be studied as an objective science. Last stated 4 years ago
10 May 2022
SP
Stephen Porges — holds since 2022-05-10 — tap for who they are
Same subject: Feeling safe is not the same as being safe: removing threat does not by itself produce the feeling. — tap to centre the map on it Feeling safe is not the same as being safe: removing threat does not by itself produce the feeling. Last stated 4 years ago
10 May 2022
SP
Stephen Porges — holds since 2022-05-10 — tap for who they are
Same subject: Psychological safety matters because it enables learning, which leads to higher performance, not because it makes people feel safe — tap to centre the map on it Psychological safety matters because it enables learning, which leads to higher performance, not because it makes people feel safe Last stated 3 weeks ago
8 Oct 2026
CM
Charity Majors — holds since 2026-10-08 — tap for who they are
Same subject: Equating an emotion with the conscious feeling of it turns emotion research into consciousness research, which is why the two must be kept apart. — tap to centre the map on it Equating an emotion with the conscious feeling of it turns emotion research into consciousness research, which is why the two must be kept apart. Last stated 2 months ago
17 Aug 2026
RA
Ralph Adolphs — holds since 2026-08-17 — tap for who they are
Same subject: Once AI starts to feel powerful rather than mistake-prone, every AI company will become far more paranoid about safety than it is today. — tap to centre the map on it Once AI starts to feel powerful rather than mistake-prone, every AI company will become far more paranoid about safety than it is today. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: We cannot know how much safety a control measure buys until we understand elicitation, so control adds a margin of unknown size. — tap to centre the map on it 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: Feelings begin as electrical fields on cell membranes, giving an organism real-time feedback on how it is doing in its environment. — tap to centre the map on it Feelings begin as electrical fields on cell membranes, giving an organism real-time feedback on how it is doing in its environment. Last stated 4 years ago
7 Sept 2022
NL
Nick Lane — holds since 2022-09-07 — 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 badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — 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 4 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — 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: Anything precise enough to benchmark is also precise enough to optimize for, and modern RL training increasingly resembles the shape of the benchmarks themselves. — tap to centre the map on it Anything precise enough to benchmark is also precise enough to optimize for, and modern RL training increasingly resembles the shape of the benchmarks themselves. Last stated 7 months ago
16 Apr 2026
SK
Sayash Kapoor — holds since 2026-04-16 — tap for who they are
At the centre
Feelings of safety have a measurable physiological basis and can be studied as an objective science.
Holds Read this korrent →
Feeling safe is not the same as being safe: removing threat does not by itself produce the feeling.
Holds
Psychological safety matters because it enables learning, which leads to higher performance, not because it makes people feel safe
Holds
Equating an emotion with the conscious feeling of it turns emotion research into consciousness research, which is why the two must be kept apart.
Holds
Once AI starts to feel powerful rather than mistake-prone, every AI company will become far more paranoid about safety than it is today.
Holds
We cannot know how much safety a control measure buys until we understand elicitation, so control adds a margin of unknown size.
Holds
Feelings begin as electrical fields on cell membranes, giving an organism real-time feedback on how it is doing in its environment.
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 badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
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
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
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
Anything precise enough to benchmark is also precise enough to optimize for, and modern RL training increasingly resembles the shape of the benchmarks themselves.
Holds