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← Diminishing returns in research are not intrinsic to the world: they…
17 connected korrents · 16 moments from 15 Jul 2021 to 20 Sept 2026.
Everything filed under AI and science
AI and science
Everything filed under LLMs
LLMs
Everything filed under innovation
innovation
Everything filed under ideas vs execution
ideas vs execution
Everything filed under ambition
ambition
Everything filed under scaling laws
scaling laws
Everything filed under patience
patience
Everything filed under design
design 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: Diminishing returns in research are not intrinsic to the world: they are what you get when the institutions around research stop changing. Diminishing returns in research are not intrinsic to the world: they are what you get when the institutions around research stop changing. Last stated 7 months ago
7 Apr 2026
MN
Michael Nielsen — holds since 2026-04-07 — tap for who they are
Same subject: A million copies of one researcher would hit diminishing returns quickly, because what research needs is people who think differently. — tap to centre the map on it A million copies of one researcher would hit diminishing returns quickly, because what research needs is people who think differently. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: Scientific and academic evaluation will shift away from published papers as the measure of output, toward valuing real-world results. — tap to centre the map on it Scientific and academic evaluation will shift away from published papers as the measure of output, toward valuing real-world results. Last stated a month ago
20 Sept 2026
DL
Daniel Lemire — holds since 2026-09-20 — tap for who they are
Same subject: A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring. — tap to centre the map on it A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring. Last stated a year ago
5 Oct 2025
AC
Albert Cheng — holds since 2025-10-05 — tap for who they are
Same subject: Returns for performance are superlinear rather than proportional across most domains that matter. — tap to centre the map on it Returns for performance are superlinear rather than proportional across most domains that matter. Last stated 3 years ago
1 Oct 2023
PG
Paul Graham — holds since 2023-10-01 — tap for who they are
Same subject: Marketing returns are fat-tailed, so paying for marketing by the hour misprices work whose value comes from a small fraction of it. — tap to centre the map on it Marketing returns are fat-tailed, so paying for marketing by the hour misprices work whose value comes from a small fraction of it. Last stated 10 months ago
9 Dec 2025
RS
Rory Sutherland — holds since 2025-12-09 — tap for who they are
Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. Last stated 7 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: Diminishing returns in science is a snapshot illusion: somebody keeps restocking the table, and new fields make progress easy again. — tap to centre the map on it Diminishing returns in science is a snapshot illusion: somebody keeps restocking the table, and new fields make progress easy again. Last stated 7 months ago
7 Apr 2026
MN
Michael Nielsen — holds since 2026-04-07 — tap for who they are
Same subject: Being average for an above-average period of time can lead to a well above-average result, because endurance rather than this year's return is the variable that matters. — tap to centre the map on it Being average for an above-average period of time can lead to a well above-average result, because endurance rather than this year's return is the variable that matters. Last stated 2 years ago
28 May 2024
MH
Morgan Housel — holds since 2024-05-28 — 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 narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. — tap to centre the map on it A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. Last stated 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — 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 11 months ago
23 Nov 2025
EH
Elliot Hershberg — holds since 2025-11-23 — 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 10 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 a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
At the centre
Diminishing returns in research are not intrinsic to the world: they are what you get when the institutions around research stop changing.
Holds Read this korrent →
A million copies of one researcher would hit diminishing returns quickly, because what research needs is people who think differently.
Holds
Scientific and academic evaluation will shift away from published papers as the measure of output, toward valuing real-world results.
Holds
A rising share of statistically insignificant experiments is the signal that a team has exploited an area too far and should go back to exploring.
Holds
Returns for performance are superlinear rather than proportional across most domains that matter.
Holds
Marketing returns are fat-tailed, so paying for marketing by the hour misprices work whose value comes from a small fraction of it.
Holds
A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from.
Holds
Diminishing returns in science is a snapshot illusion: somebody keeps restocking the table, and new fields make progress easy again.
Holds
Being average for an above-average period of time can lead to a well above-average result, because endurance rather than this year's return is the variable that matters.
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 narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next.
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
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