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← Technological progress looks smooth and exponential from a distance…
17 connected korrents · 17 moments on record from 26 Aug 2022 to 3 Sept 2026.
Everything filed under benchmarks
benchmarks
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Everything filed under reinforcement learning
reinforcement learning
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innovation
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scaling laws
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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 Same subject Same subject Read this korrent: Technological progress looks smooth and exponential from a distance but is actually made of individual S-curves up close. Technological progress looks smooth and exponential from a distance but is actually made of individual S-curves up close. Last stated 3 years ago
9 Feb 2024
TU
Tim Urban — holds since 2024-02-09 — tap for who they are
Same subject: The thing worth finding is the exponential with the steepest curve that will run the longest — decades ago that was Moore’s law, and today it is AI progress. — tap to centre the map on it The thing worth finding is the exponential with the steepest curve that will run the longest — decades ago that was Moore’s law, and today it is AI progress. Last stated 2 months ago
29 Jul 2026
AW
Alexandr Wang — holds since 2026-07-29 — tap for who they are
Same subject: The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. — tap to centre the map on it The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed. Last stated 6 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: Long-run GDP charts hide what matters: technologies are contingent and path dependent, so the same number can describe economies that work in entirely different ways. — tap to centre the map on it Long-run GDP charts hide what matters: technologies are contingent and path dependent, so the same number can describe economies that work in entirely different ways. Last stated 4 years ago
26 Aug 2022
BD
Bret Devereaux — holds since 2022-08-26 — tap for who they are
Same subject: An exponential feels like it cannot possibly keep going, which is exactly why people keep expecting AI progress to stop. — tap to centre the map on it An exponential feels like it cannot possibly keep going, which is exactly why people keep expecting AI progress to stop. Last stated 3 months ago
10 Jun 2026
MZ
Mark Zuckerberg — holds since 2026-06-10 — tap for who they are
Same subject: Expecting technology to keep accelerating is a bias of our particular moment; for most of human history the tools did not change at all. — tap to centre the map on it Expecting technology to keep accelerating is a bias of our particular moment; for most of human history the tools did not change at all. Last stated 2 years ago
22 Dec 2024
AF
Adam Frank — holds since 2024-12-22 — tap for who they are
Same subject: Technological development trajectories often display increasing returns, which entrench early paths and crowd out alternatives. — tap to centre the map on it Technological development trajectories often display increasing returns, which entrench early paths and crowd out alternatives. Last stated 4 weeks ago
27 Aug 2026
HF
Henry Farrell — holds since 2026-08-27 — tap for who they are
Same subject: We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it. — tap to centre the map on it We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Marketing channels do not settle onto a plateau; after the S-curve they sag, which is why the shape is an elephant and not an S. — tap to centre the map on it Marketing channels do not settle onto a plateau; after the S-curve they sag, which is why the shape is an elephant and not an S. Last stated 8 months ago
25 Jan 2026
JC
Jason Cohen — holds since 2026-01-25 — tap for who they are
Same subject: A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. — tap to centre the map on it A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. Last stated 3 weeks ago
3 Sept 2026
DR
Dax Raad — holds since 2026-09-03 — tap for who they are
Same subject: A carmaker's claim to be the safest is mostly an artefact of comparing a new car against a fleet average twelve years old. — tap to centre the map on it A carmaker's claim to be the safest is mostly an artefact of comparing a new car against a fleet average twelve years old. Last stated 3 years ago
19 Dec 2023
PK
Philip Koopman — holds since 2023-12-19 — tap for who they are
Same subject: A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost. — tap to centre the map on it A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost. Last stated 6 months ago
1 Apr 2026
TP
Thuan Pham — holds since 2026-04-01 — 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 10 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 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 2 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. — tap to centre the map on it A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. Last stated a month ago
10 Aug 2026
FL
Fei-Fei Li — holds since 2026-08-10 — tap for who they are
At the centre
Technological progress looks smooth and exponential from a distance but is actually made of individual S-curves up close.
Holds Read this korrent →
The thing worth finding is the exponential with the steepest curve that will run the longest — decades ago that was Moore’s law, and today it is AI progress.
Holds
The scaling curve really is S-shaped, but there are at least two cycles left in it, which means models sixteen times smarter and all knowledge work subsumed.
Holds
Long-run GDP charts hide what matters: technologies are contingent and path dependent, so the same number can describe economies that work in entirely different ways.
Holds
An exponential feels like it cannot possibly keep going, which is exactly why people keep expecting AI progress to stop.
Holds
Expecting technology to keep accelerating is a bias of our particular moment; for most of human history the tools did not change at all.
Holds
Technological development trajectories often display increasing returns, which entrench early paths and crowd out alternatives.
Holds
We are already in an intelligence explosion and have been for decades, so AI will show up as more of the same exponential rather than a break in it.
Holds
Marketing channels do not settle onto a plateau; after the S-curve they sag, which is why the shape is an elephant and not an S.
Holds
A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year.
Holds
A carmaker's claim to be the safest is mostly an artefact of comparing a new car against a fleet average twelve years old.
Holds
A company's staff-engineer bar should be set against the best companies in the industry rather than against its own history, which is what makes title inflation a real cost.
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 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 child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved.
Holds