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← Human parity on discovery benchmarks like DiG-bench will be reached by…
17 connected korrents · 18 moments from 15 Jul 2021 to 27 Sept 2026. Nearly all of them are about recursive self-improvement .
Everything filed under AI and science
AI and science
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benchmarks
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AGI
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world models
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LLMs 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: Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off. Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off. Last stated 2 months ago
17 Aug 2026
JC
Jack Clark — holds since 2026-08-17 — tap for who they are
Same subject: AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started. — tap to centre the map on it AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started. Last stated 2 months ago
3 Aug 2026
CP
Chamath Palihapitiya — holds since 2026-08-03 — tap for who they are
Same subject: AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. — tap to centre the map on it AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: Coding agents already do coarse-grained recursive self-improvement, because every use rewrites their instruction files and their long-term memory. — tap to centre the map on it Coding agents already do coarse-grained recursive self-improvement, because every use rewrites their instruction files and their long-term memory. Last stated 2 months ago
26 Jul 2026
JH
Jensen Huang — holds since 2026-07-26 — tap for who they are
Same subject: Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop. — tap to centre the map on it Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop. Last stated 2 months ago
10 Aug 2026
FC
François Chollet — holds since 2026-08-10 — tap for who they are
Same subject: Internal models at top labs are improving faster than public ones and have begun early recursive self-improvement. — tap to centre the map on it Internal models at top labs are improving faster than public ones and have begun early recursive self-improvement. Last stated 3 weeks ago
14 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-14 — tap for who they are
Same subject: Recursive self-improvement (RSI) may not lead to runaway superintelligence without a major conceptual breakthrough. — tap to centre the map on it Recursive self-improvement (RSI) may not lead to runaway superintelligence without a major conceptual breakthrough. Last stated 5 days ago
27 Sept 2026
RN
Ramez Naam — holds since 2026-09-27 — tap for who they are
Same subject: Recursive self-improvement has already started, because AI research itself is now being automated. — tap to centre the map on it Recursive self-improvement has already started, because AI research itself is now being automated. Last stated 3 weeks ago
13 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-13 — tap for who they are
JL
Jan Leike — holds since 2026-01-22 — tap for who they are
Same subject: Recursive self-improvement in AI will mainly make existing model capability cheaper rather than raise peak intelligence. — tap to centre the map on it Recursive self-improvement in AI will mainly make existing model capability cheaper rather than raise peak intelligence. Last stated 2 weeks ago
19 Sept 2026
NL
Nathan Lambert — holds since 2026-09-19 — tap for who they are
Same subject: A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. — tap to centre the map on it A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. Last stated 2 years ago
13 May 2024
DL
Derek Lowe — holds since 2024-05-13 — tap for who they are
Same subject: A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. — tap to centre the map on it A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. Last stated 2 years ago
17 Sept 2024
AT
Alex Telford — holds since 2024-09-17 — tap for who they are
Same subject: A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. — tap to centre the map on it A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — 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 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: Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. — tap to centre the map on it Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. — tap to centre the map on it AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. Last stated 10 months ago
23 Nov 2025
EH
Elliot Hershberg — holds since 2025-11-23 — tap for who they are
Same subject: AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work. — tap to centre the map on it AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work. Last stated 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
At the centre
Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off.
Holds Read this korrent →
AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started.
Holds
AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate.
Holds
Coding agents already do coarse-grained recursive self-improvement, because every use rewrites their instruction files and their long-term memory.
Holds
Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop.
Holds
Internal models at top labs are improving faster than public ones and have begun early recursive self-improvement.
Holds
Recursive self-improvement (RSI) may not lead to runaway superintelligence without a major conceptual breakthrough.
Holds
Recursive self-improvement has already started, because AI research itself is now being automated.
Holds
Recursive self-improvement in AI will mainly make existing model capability cheaper rather than raise peak intelligence.
Holds
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Holds
A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck.
Holds
A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known.
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 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
Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics.
Holds
AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points.
Holds
AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work.
Holds