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← A priori arguments on empirical matters, such as that AI will…
17 connected korrents · 17 moments from 7 Nov 2014 to 26 Sept 2026.
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government 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: A priori arguments on empirical matters, such as that AI will certainly kill everyone, are usually wrong however convincing they seem. A priori arguments on empirical matters, such as that AI will certainly kill everyone, are usually wrong however convincing they seem. Last stated 3 years ago
by 27 Dec 2023
NQ
Nabeel S. Qureshi — holds since 2023-12-27 — tap for who they are
Same subject: There is a good chance that AI will kill everyone soon. — tap to centre the map on it There is a good chance that AI will kill everyone soon. Last stated 3 weeks ago
11 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-11 — tap for who they are
Same subject: Fear of strong AI models killing everyone was not based on peer-reviewed research showing high doom odds, nor indicated by market prices. — tap to centre the map on it Fear of strong AI models killing everyone was not based on peer-reviewed research showing high doom odds, nor indicated by market prices. Last stated a week ago
26 Sept 2026
TC
Tyler Cowen — holds since 2026-09-26 — tap for who they are
Same subject: AI will likely kill some people on the way to killing all of humanity. — tap to centre the map on it AI will likely kill some people on the way to killing all of humanity. Last stated 3 weeks ago
13 Sept 2026
NR
Naval Ravikant — holds since 2026-09-13 — tap for who they are
Same subject: Arguing that human-level AI is very unlikely within twenty years is now the minority position, and the burden of proof has moved onto it. — tap to centre the map on it Arguing that human-level AI is very unlikely within twenty years is now the minority position, and the burden of proof has moved onto it. Last stated 2 years ago
1 Apr 2025
HT
Helen Toner — holds since 2025-04-01 — tap for who they are
Same subject: If AI is risky like fire, everyone should have it; if it is risky like a nuclear weapon, no one should. — tap to centre the map on it If AI is risky like fire, everyone should have it; if it is risky like a nuclear weapon, no one should. Last stated 3 weeks ago
16 Sept 2026
NR
Naval Ravikant — holds since 2026-09-16 — tap for who they are
Same subject: Arguing that nobody should have powerful AI is a respectable position; arguing that only trusted authorities should have it is not. — tap to centre the map on it Arguing that nobody should have powerful AI is a respectable position; arguing that only trusted authorities should have it is not. Last stated 3 years ago
29 Jun 2023
GH
George Hotz — holds since 2023-06-29 — tap for who they are
Same subject: "There is no empirical evidence against my position" is not an argument for it. — tap to centre the map on it "There is no empirical evidence against my position" is not an argument for it. Last stated 12 years ago
7 Nov 2014
DL
Dan Luu — holds since 2014-11-07 — tap for who they are
Same subject: Technologies are almost always preceded by slightly worse versions of themselves, and there is no reason for AI to be the exception. — tap to centre the map on it Technologies are almost always preceded by slightly worse versions of themselves, and there is no reason for AI to be the exception. Last stated 9 years ago
24 Feb 2018
PC
Paul Christiano — holds since 2018-02-24 — 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 2 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 2 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 3 weeks 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
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 9 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 3 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 3 weeks ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
At the centre
A priori arguments on empirical matters, such as that AI will certainly kill everyone, are usually wrong however convincing they seem.
Holds Read this korrent →
There is a good chance that AI will kill everyone soon.
Holds
Fear of strong AI models killing everyone was not based on peer-reviewed research showing high doom odds, nor indicated by market prices.
Holds
AI will likely kill some people on the way to killing all of humanity.
Holds
Arguing that human-level AI is very unlikely within twenty years is now the minority position, and the burden of proof has moved onto it.
Holds
If AI is risky like fire, everyone should have it; if it is risky like a nuclear weapon, no one should.
Holds
Arguing that nobody should have powerful AI is a respectable position; arguing that only trusted authorities should have it is not.
Holds
"There is no empirical evidence against my position" is not an argument for it.
Holds
Technologies are almost always preceded by slightly worse versions of themselves, and there is no reason for AI to be the exception.
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
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