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← Computational irreducibility is ubiquitous, affecting essentially any system whose behavior is not obviously simple.
17 connected korrents · 12 moments from 15 Jul 2021 to 17 Aug 2026.
Everything filed under AI and science
AI and science
Everything filed under mathematics
mathematics
Everything filed under simplicity
simplicity
Everything filed under design
design
Everything filed under Google
Google
Everything filed under evolutionary biology
evolutionary biology
Everything filed under infrastructure
infrastructure 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: Computational irreducibility is ubiquitous, affecting essentially any system whose behavior is not obviously simple. Computational irreducibility is ubiquitous, affecting essentially any system whose behavior is not obviously simple. Last stated 2 months ago
21 Jul 2026
SW
Stephen Wolfram — holds since 2026-07-21 — tap for who they are
Same subject: The behavior of the simplest computational rules is permanently foundational, not merely significant for the present. — tap to centre the map on it The behavior of the simplest computational rules is permanently foundational, not merely significant for the present. Last stated 9 months ago
12 Jan 2026
SW
Stephen Wolfram — holds since 2026-01-12 — tap for who they are
Same subject: A program is only worth running if its behavior cannot be fully foreseen in advance. — tap to centre the map on it A program is only worth running if its behavior cannot be fully foreseen in advance. Last stated 2 months ago
21 Jul 2026
SW
Stephen Wolfram — holds since 2026-07-21 — tap for who they are
Same subject: Studying what arbitrary computational rules do is a distinct science, separate from computer science and mathematics. — tap to centre the map on it Studying what arbitrary computational rules do is a distinct science, separate from computer science and mathematics. Last stated 9 months ago
12 Jan 2026
SW
Stephen Wolfram — holds since 2026-01-12 — tap for who they are
Same subject: A program's simplicity of structure does not limit how sophisticated the computation it performs can be. — tap to centre the map on it A program's simplicity of structure does not limit how sophisticated the computation it performs can be. Last stated 2 months ago
21 Jul 2026
SW
Stephen Wolfram — holds since 2026-07-21 — tap for who they are
Same subject: The behavior of very simple computational rules can require large amounts of obscure mathematics to fully capture. — tap to centre the map on it The behavior of very simple computational rules can require large amounts of obscure mathematics to fully capture. Last stated 9 months ago
12 Jan 2026
SW
Stephen Wolfram — holds since 2026-01-12 — tap for who they are
Same subject: In a system built from interacting components, complexity is multiplicative: making one part more complex adds complexity elsewhere too. — tap to centre the map on it In a system built from interacting components, complexity is multiplicative: making one part more complex adds complexity elsewhere too. Last stated 3 years ago
6 Dec 2023
RP
Rob Pike — holds since 2023-12-06 — tap for who they are
Same subject: Computation sits at the top of reality, not at its base: it is something our biosphere built after billions of years of evolution. — tap to centre the map on it Computation sits at the top of reality, not at its base: it is something our biosphere built after billions of years of evolution. Last stated 2 years ago
13 Jun 2024
SW
Sara Walker — holds since 2024-06-13 — tap for who they are
Same subject: Making a change within a complex system tends to produce unforeseen and unintended consequences. — tap to centre the map on it Making a change within a complex system tends to produce unforeseen and unintended consequences. Last stated 4 years ago
30 May 2022
SC
Steve Coast — holds since 2022-05-30 — 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: 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
Same subject: As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. — tap to centre the map on it As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. Last stated 2 months ago
17 Aug 2026
JC
Jack Clark — holds since 2026-08-17 — tap for who they are
Same subject: 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. — tap to centre the map on it 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: Today's AI systems are significantly under-elicited for their ability to automate AI R&D. — tap to centre the map on it Today's AI systems are significantly under-elicited for their ability to automate AI R&D. Last stated 2 months ago
10 Aug 2026
JC
Jack Clark — holds since 2026-08-10 — tap for who they are
At the centre
Computational irreducibility is ubiquitous, affecting essentially any system whose behavior is not obviously simple.
Holds Read this korrent →
The behavior of the simplest computational rules is permanently foundational, not merely significant for the present.
Holds
A program is only worth running if its behavior cannot be fully foreseen in advance.
Holds
Studying what arbitrary computational rules do is a distinct science, separate from computer science and mathematics.
Holds
A program's simplicity of structure does not limit how sophisticated the computation it performs can be.
Holds
The behavior of very simple computational rules can require large amounts of obscure mathematics to fully capture.
Holds
In a system built from interacting components, complexity is multiplicative: making one part more complex adds complexity elsewhere too.
Holds
Computation sits at the top of reality, not at its base: it is something our biosphere built after billions of years of evolution.
Holds
Making a change within a complex system tends to produce unforeseen and unintended consequences.
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
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
As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves.
Holds
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
Today's AI systems are significantly under-elicited for their ability to automate AI R&D.
Holds