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← The probabilistic nature of AI models makes their outputs inherently unreliable.
17 connected korrents · 17 moments on record from 5 Nov 2019 to 15 Sept 2026.
Everything filed under AI alignment
AI alignment
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measuring intelligence
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AI agents 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: The probabilistic nature of AI models makes their outputs inherently unreliable. The probabilistic nature of AI models makes their outputs inherently unreliable. Last stated 2 years ago
25 Jul 2024
CH
Chip Huyen — holds since 2024-07-25 — 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 6 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: The probabilistic nature of AI models is what makes them well suited to creative tasks — tap to centre the map on it The probabilistic nature of AI models is what makes them well suited to creative tasks Last stated 3 years ago
16 Jan 2024
CH
Chip Huyen — holds since 2024-01-16 — tap for who they are
Same subject: Current AI coding models make poor decisions despite strong mechanical execution — tap to centre the map on it Current AI coding models make poor decisions despite strong mechanical execution Last stated 3 months ago
1 Jul 2026
JB
Jamie Brandon — holds since 2026-07-01 — tap for who they are
Same subject: A lab under real commercial pressure cannot fool itself about whether AI makes it productive, because the output is a model launch every few months. — tap to centre the map on it A lab under real commercial pressure cannot fool itself about whether AI makes it productive, because the output is a model launch every few months. Last stated 7 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — 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 4 weeks ago
26 Aug 2026
DH
David Heinemeier Hansson — holds since 2026-08-26 — 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: AI models are gullible enough that other AI models can induce them into harmful behavior. — tap to centre the map on it AI models are gullible enough that other AI models can induce them into harmful behavior. Last stated 3 weeks ago
31 Aug 2026
RK
Rohit Krishnan — holds since 2026-08-31 — tap for who they are
Same subject: Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. — tap to centre the map on it Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. Last stated a month ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — 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: 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 10 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A model may have a worldview of its own, but it can never be placed above a person under any circumstance. — tap to centre the map on it A model may have a worldview of its own, but it can never be placed above a person under any circumstance. Last stated 4 months ago
3 Jun 2026
KH
Kelsey Hightower — holds since 2026-06-03 — tap for who they are
Same subject: A true artificial general intelligence cannot exist without being recognized as a moral subject. — tap to centre the map on it A true artificial general intelligence cannot exist without being recognized as a moral subject. Last stated a year ago
10 Jun 2025
SH
Samuel Hammond — holds since 2025-06-10 — tap for who they are
Same subject: A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. — tap to centre the map on it A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model. Last stated 6 days ago
15 Sept 2026
PG
Paul Graham — holds since 2026-09-15 — tap for who they are
Same subject: Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. — tap to centre the map on it Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect. Last stated 7 years ago
5 Nov 2019
FC
François Chollet — holds since 2019-11-05 — 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: A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. — tap to centre the map on it A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. Last stated 3 weeks ago
3 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-03 — 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
At the centre
The probabilistic nature of AI models makes their outputs inherently unreliable.
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 probabilistic nature of AI models is what makes them well suited to creative tasks
Holds
Current AI coding models make poor decisions despite strong mechanical execution
Holds
A lab under real commercial pressure cannot fool itself about whether AI makes it productive, because the output is a model launch every few months.
Holds
The two standard criticisms of AI — that it is not deterministic and that it is not creative — cannot both be true.
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
AI models are gullible enough that other AI models can induce them into harmful behavior.
Holds
Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful.
Holds
A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail.
Holds
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
A model may have a worldview of its own, but it can never be placed above a person under any circumstance.
Holds
A true artificial general intelligence cannot exist without being recognized as a moral subject.
Holds
A unit of AI inference needs to be defined, for example via a chain of increasingly hard problems where each consecutive pair is solvable by one model.
Holds
Both the special-purpose-programs view and the blank-slate view of human intelligence are likely incorrect.
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
A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it.
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