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← Build where today's models succeed one percent of the time, not…
8 connected korrents · 8 moments on record from 19 Jun 2024 to 12 Aug 2026.
Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. Last stated a month ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Before building on a gap in the general models, work out whether that gap survives six months or three years. — tap to centre the map on it Before building on a gap in the general models, work out whether that gap survives six months or three years. Last stated a month ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: The one safe bet about AI is that models will improve, so what a company has to build is an organisation that gets better as models get better. — tap to centre the map on it The one safe bet about AI is that models will improve, so what a company has to build is an organisation that gets better as models get better. Last stated 11 months ago
16 Oct 2025
DF
Dylan Field — holds since 2025-10-16 — tap for who they are
Same subject: Open-sourcing capable models matters because it is the only thing standing between us and a world where two or three companies control the frontier. — tap to centre the map on it Open-sourcing capable models matters because it is the only thing standing between us and a world where two or three companies control the frontier. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
Same subject: Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. — tap to centre the map on it Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Today's AI tools either solve a problem or fail at it, and are really bad at partial progress or at identifying which intermediate step to attack first. — tap to centre the map on it Today's AI tools either solve a problem or fail at it, and are really bad at partial progress or at identifying which intermediate step to attack first. Last stated 6 months ago
20 Mar 2026
TT
Terence Tao — holds since 2026-03-20 — tap for who they are
Same subject: Economic growth from AI waits on change management, not on model capability: the work artifact and the workflow have to change first. — tap to centre the map on it Economic growth from AI waits on change management, not on model capability: the work artifact and the workflow have to change first. Last stated 10 months ago
12 Nov 2025
SN
Satya Nadella — holds since 2025-11-12 — tap for who they are
Same subject: The way to find what a model can do is to hand it tasks slightly harder than you believe it can handle. — tap to centre the map on it The way to find what a model can do is to hand it tasks slightly harder than you believe it can handle. Last stated a month ago
27 Jul 2026
BC
Boris Cherny — holds since 2026-07-27 — tap for who they are
Same subject: Today's models are severely under-elicited: they are far more capable than the way we currently ask them makes them look. — tap to centre the map on it Today's models are severely under-elicited: they are far more capable than the way we currently ask them makes them look. Last stated 2 years ago
8 Nov 2024
JL
Jan Leike — holds since 2024-11-08 — tap for who they are