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← That people are good at maths and coding, which evolution never…
17 connected korrents · 16 moments from 15 Jul 2021 to 8 Oct 2026.
Everything filed under mathematics
mathematics
Everything filed under evolutionary biology
evolutionary biology
Everything filed under AI and science
AI and science
Everything filed under formal proof
formal proof
Everything filed under LLMs
LLMs
Everything filed under scaling laws
scaling laws
Everything filed under AI and human skill
AI and human skill
Everything filed under coding agents
coding 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: That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental. That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution. — tap to centre the map on it Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution. Last stated 8 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — tap for who they are
Same subject: Humans are no longer the sole producers of math that is incomprehensible to others and potentially incorrect — tap to centre the map on it Humans are no longer the sole producers of math that is incomprehensible to others and potentially incorrect Last stated 2 weeks ago
8 Oct 2026
NS
Noah Smith — holds since 2026-10-08 — tap for who they are
Same subject: Anyone who knew how to code before AI is having a way better time using AI than someone who did not, because they know the right words to say. — tap to centre the map on it Anyone who knew how to code before AI is having a way better time using AI than someone who did not, because they know the right words to say. Last stated 6 months ago
14 Apr 2026
BL
Brian Lovin — holds since 2026-04-14 — tap for who they are
Same subject: Programmers fail to recognise how much mathematics their job uses because the mathematics it needs is discrete and school teaches the continuous kind. — tap to centre the map on it Programmers fail to recognise how much mathematics their job uses because the mathematics it needs is discrete and school teaches the continuous kind. Last stated 3 months ago
29 Jul 2026
HW
Hillel Wayne — holds since 2026-07-29 — tap for who they are
Same subject: Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. — tap to centre the map on it Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Last stated a year ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
Same subject: Intelligence is becoming a choice rather than a byproduct of daily work: there will still be smart people, but only those who choose to be. — tap to centre the map on it Intelligence is becoming a choice rather than a byproduct of daily work: there will still be smart people, but only those who choose to be. Last stated 11 months ago
18 Nov 2025
PG
Paul Graham — holds since 2024-10-01 — tap for who they are
SY
Scott H. Young — holds since 2025-11-18 — tap for who they are
Same subject: Being an excellent programmer is a burden rather than an advantage when learning to work with coding agents. — tap to centre the map on it Being an excellent programmer is a burden rather than an advantage when learning to work with coding agents. Last stated 8 months ago
12 Feb 2026
LF
Lex Fridman — holds since 2026-02-12 — tap for who they are
Same subject: What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. — tap to centre the map on it What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use. Last stated 7 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: A selection signal can be validated without a significance threshold, by measuring how far it is enriched for mutations an entirely independent study says affect a trait. — tap to centre the map on it A selection signal can be validated without a significance threshold, by measuring how far it is enriched for mutations an entirely independent study says affect a trait. Last stated 5 months ago
8 May 2026
DR
David Reich — holds since 2026-05-08 — tap for who they are
Same subject: Adaptive evolution tends to achieve even a simple, fixed objective through complicated behavior. — tap to centre the map on it Adaptive evolution tends to achieve even a simple, fixed objective through complicated behavior. Last stated 5 months ago
4 Jun 2026
SW
Stephen Wolfram — holds since 2026-06-04 — tap for who they are
Same subject: Animal species with the least individual struggle and the most mutual aid are invariably the most numerous and prosperous — tap to centre the map on it Animal species with the least individual struggle and the most mutual aid are invariably the most numerous and prosperous
PK
Peter Kropotkin — holds since c. 1890–1902 — 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 test checks a handful of examples; a proof settles an infinite state space, which is why formal methods can say things testing never can. — tap to centre the map on it A test checks a handful of examples; a proof settles an infinite state space, which is why formal methods can say things testing never can. Last stated 6 months ago
22 Apr 2026
MK
Martin Kleppmann — holds since 2026-04-22 — tap for who they are
Same subject: AI is making formal methods more popular without making them mainstream, moving them from about a tenth of a per cent of engineers to three tenths. — tap to centre the map on it AI is making formal methods more popular without making them mainstream, moving them from about a tenth of a per cent of engineers to three tenths. Last stated 3 months ago
29 Jul 2026
HW
Hillel Wayne — holds since 2026-07-29 — tap for who they are
Same subject: Engineers are sceptical of formal methods because they were burned by CASE and UML, sold as miracle solutions and imposed on them regardless of fit. — tap to centre the map on it Engineers are sceptical of formal methods because they were burned by CASE and UML, sold as miracle solutions and imposed on them regardless of fit. Last stated 3 months ago
29 Jul 2026
HW
Hillel Wayne — holds since 2026-07-29 — tap for who they are
At the centre
That people are good at maths and coding, which evolution never selected for, shows human learning is not a complicated evolutionary prior but something more fundamental.
Holds Read this korrent →
Pre-training is not the process by which humans learn; it sits somewhere between human learning and human evolution.
Holds
Humans are no longer the sole producers of math that is incomprehensible to others and potentially incorrect
Holds
Anyone who knew how to code before AI is having a way better time using AI than someone who did not, because they know the right words to say.
Holds
Programmers fail to recognise how much mathematics their job uses because the mathematics it needs is discrete and school teaches the continuous kind.
Holds
Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff.
Holds
Intelligence is becoming a choice rather than a byproduct of daily work: there will still be smart people, but only those who choose to be.
Holds
Being an excellent programmer is a burden rather than an advantage when learning to work with coding agents.
Holds
What AI still cannot do in mathematics is build cumulatively on partial progress; it is trial, error and brute force rather than an idea improving through use.
Holds
A selection signal can be validated without a significance threshold, by measuring how far it is enriched for mutations an entirely independent study says affect a trait.
Holds
Adaptive evolution tends to achieve even a simple, fixed objective through complicated behavior.
Holds
Animal species with the least individual struggle and the most mutual aid are invariably the most numerous and prosperous
Last stated c. 1890–1902
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 test checks a handful of examples; a proof settles an infinite state space, which is why formal methods can say things testing never can.
Holds
AI is making formal methods more popular without making them mainstream, moving them from about a tenth of a per cent of engineers to three tenths.
Holds
Engineers are sceptical of formal methods because they were burned by CASE and UML, sold as miracle solutions and imposed on them regardless of fit.
Holds