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← People have grown accustomed to AI being non-deterministic and…
17 connected korrents · 15 moments from 9 Aug 2022 to 21 Sept 2026.
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design 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: People have grown accustomed to AI being non-deterministic and occasionally wrong, so it carries little brand risk anymore. People have grown accustomed to AI being non-deterministic and occasionally wrong, so it carries little brand risk anymore. Last stated 2 weeks ago
18 Sept 2026
HD
Horace Dediu — holds since 2026-09-18 — tap for who they are
Same subject: AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough. — tap to centre the map on it AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough. Last stated 7 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: The two standard criticisms of AI — that it is not deterministic and that it is not creative — cannot both be true. — tap to centre the map on it The two standard criticisms of AI — that it is not deterministic and that it is not creative — cannot both be true. Last stated a month ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — tap for who they are
Same subject: The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly. — tap to centre the map on it The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Widespread tolerance for AI being wrong means adding AI features to a product carries little brand risk as long as it behaves as expected. — tap to centre the map on it Widespread tolerance for AI being wrong means adding AI features to a product carries little brand risk as long as it behaves as expected. Last stated 2 weeks ago
21 Sept 2026
HD
Horace Dediu — holds since 2026-09-21 — tap for who they are
Same subject: The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it. — tap to centre the map on it The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: There is no route to AI alignment or safety that goes around reliability: a system that cannot reliably follow a known algorithm cannot be made safe. — tap to centre the map on it There is no route to AI alignment or safety that goes around reliability: a system that cannot reliably follow a known algorithm cannot be made safe. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: The least verifiable part of AI research is the judgement call about what goes into the one big training run. — tap to centre the map on it The least verifiable part of AI research is the judgement call about what goes into the one big training run. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Consumer AI that is right 90% of the time delights people; industrial AI that is right 90% of the time is 100% dissatisfaction. — tap to centre the map on it Consumer AI that is right 90% of the time delights people; industrial AI that is right 90% of the time is 100% dissatisfaction. Last stated 9 months ago
8 Jan 2026
JH
Jensen Huang — holds since 2026-01-08 — tap for who they are
Same subject: A belief system combining cosmic stakes, privileged knowledge, personal vocation and an imperative to act can license extraordinary behavior when it conflicts with ordinary constraints. — tap to centre the map on it A belief system combining cosmic stakes, privileged knowledge, personal vocation and an imperative to act can license extraordinary behavior when it conflicts with ordinary constraints. Last stated 2 weeks ago
17 Sept 2026
VR
Venkatesh Rao — holds since 2026-09-17 — tap for who they are
Same subject: A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally. — tap to centre the map on it A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally. Last stated 8 months ago
25 Jan 2026
JC
Jason Cohen — holds since 2026-01-25 — tap for who they are
Same subject: A decision cannot be judged by its outcome, because good decisions fail through no fault of the decider and bad ones succeed by luck. — tap to centre the map on it A decision cannot be judged by its outcome, because good decisions fail through no fault of the decider and bad ones succeed by luck. Last stated 4 years ago
9 Aug 2022
GK
Gary Klein — holds since 2022-08-09 — tap for who they are
Same subject: A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. — tap to centre the map on it A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. — tap to centre the map on it Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Agents are going to be incorporated into mainstream interfaces — tap to centre the map on it Agents are going to be incorporated into mainstream interfaces Last stated 6 months ago
25 Mar 2026
DH
David Heinemeier Hansson — holds since 2026-03-25 — tap for who they are
Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. Last stated 10 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — 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 3 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 7 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
At the centre
People have grown accustomed to AI being non-deterministic and occasionally wrong, so it carries little brand risk anymore.
Holds Read this korrent →
AI's business results are lagging because organisations have a low tolerance for non-determinism, not because the models are not good enough.
Holds
The two standard criticisms of AI — that it is not deterministic and that it is not creative — cannot both be true.
Holds
The likeliest bad path is not a coup but sloppiness: AI does everything verifiable well, research races ahead, and the subtle work of keeping AI safe is what gets done badly.
Holds
Widespread tolerance for AI being wrong means adding AI features to a product carries little brand risk as long as it behaves as expected.
Holds
The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it.
Holds
There is no route to AI alignment or safety that goes around reliability: a system that cannot reliably follow a known algorithm cannot be made safe.
Holds
The least verifiable part of AI research is the judgement call about what goes into the one big training run.
Holds
Consumer AI that is right 90% of the time delights people; industrial AI that is right 90% of the time is 100% dissatisfaction.
Holds
A belief system combining cosmic stakes, privileged knowledge, personal vocation and an imperative to act can license extraordinary behavior when it conflicts with ordinary constraints.
Holds
A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally.
Holds
A decision cannot be judged by its outcome, because good decisions fail through no fault of the decider and bad ones succeed by luck.
Holds
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers.
Holds
Agents are going to be incorporated into mainstream interfaces
Holds
"Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next.
Holds
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds
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