Tap a claim on the ring to put it at the centre.
← A physical AI company needs three AIs, not one — the agent, the…
17 connected korrents · 15 moments from 3 Feb 2025 to 12 Oct 2026.
Everything filed under reinforcement learning
reinforcement learning
Everything filed under AI agents
AI agents
Everything filed under robotics
robotics
Everything filed under scaling laws
scaling laws
Everything filed under LLMs
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: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated 3 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: Physical AI has to make far fewer mistakes than any AI deployed so far, because it is only useful when it acts autonomously on the world. — tap to centre the map on it Physical AI has to make far fewer mistakes than any AI deployed so far, because it is only useful when it acts autonomously on the world. Last stated 2 months ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it. — tap to centre the map on it AI will not run out of data, because there is already enough real-world data to build the simulators that generate more of it. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. — tap to centre the map on it A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. Last stated 3 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: AI agents trained on an expert's published work can only automate a small fraction of that expert's actual job. — tap to centre the map on it AI agents trained on an expert's published work can only automate a small fraction of that expert's actual job. Last stated 11 months ago
27 Nov 2025
BG
Brendan Gregg — holds since 2025-11-27 — tap for who they are
Same subject: Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. — tap to centre the map on it Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model. Last stated 3 months ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: AI agents will solve problems by building software on the fly, creating a market of software and data for agents to pay for — tap to centre the map on it AI agents will solve problems by building software on the fly, creating a market of software and data for agents to pay for Last stated 2 weeks ago
12 Oct 2026
PL
Pieter Levels — holds since 2026-10-12 — tap for who they are
Same subject: An application-layer AI company's real breakthroughs come from going a click or two down the stack rather than from using the models as they are. — tap to centre the map on it An application-layer AI company's real breakthroughs come from going a click or two down the stack rather than from using the models as they are. Last stated a year ago
18 Aug 2025
CB
Clay Bavor — holds since 2025-08-18 — tap for who they are
Same subject: AI sales agents do not work out of the box; the training is the product. — tap to centre the map on it AI sales agents do not work out of the box; the training is the product. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. — tap to centre the map on it A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score. Last stated 2 months ago
26 Aug 2026
HK
Henrik Karlsson — holds since 2026-08-26 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 11 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Building intuition for what works and what does not comes from taking a lot of shots at the goal. — tap to centre the map on it Building intuition for what works and what does not comes from taking a lot of shots at the goal. Last stated 7 months ago
12 Mar 2026
JP
Josh Puckett — holds since 2026-03-12 — tap for who they are
Same subject: Current models are unsafe because they are not smart enough, not because they are too smart. — tap to centre the map on it Current models are unsafe because they are not smart enough, not because they are too smart. Last stated a month ago
13 Sept 2026
FC
François Chollet — holds since 2026-09-13 — tap for who they are
Same subject: Humans keep their place in AI as judges rather than authors, because telling which of two answers is better is far easier than writing a good one. — tap to centre the map on it Humans keep their place in AI as judges rather than authors, because telling which of two answers is better is far easier than writing a good one. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: If whole categories of reward hack are undetectable by humans, then training against the hacks we do catch teaches models to cheat only where we cannot see. — tap to centre the map on it If whole categories of reward hack are undetectable by humans, then training against the hacks we do catch teaches models to cheat only where we cannot see. Last stated 2 months ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: Models resemble each other because pre-training is the same everywhere; what differentiates labs now is RL and post-training. — tap to centre the map on it Models resemble each other because pre-training is the same everywhere; what differentiates labs now is RL and post-training. 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 a crappy evolution: the practically buildable substitute for the process that gave animals their built-in hardware. — tap to centre the map on it Pre-training is a crappy evolution: the practically buildable substitute for the process that gave animals their built-in hardware. Last stated a year ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: Reinforcement learning from verifiable rewards does not reliably carry a model's pretrained ethical understanding into its actual behavior. — tap to centre the map on it Reinforcement learning from verifiable rewards does not reliably carry a model's pretrained ethical understanding into its actual behavior. Last stated 2 months ago
11 Aug 2026
SH
Samuel Hammond — holds since 2026-08-11 — tap for who they are