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← In the near term, more capable models should mean safer models.
17 connected korrents · 15 moments on record from 24 Jun 2023 to 13 Sept 2026.
Everything filed under neural networks
neural networks
Everything filed under scaling laws
scaling laws
Everything filed under reinforcement learning
reinforcement learning
Everything filed under cybersecurity
cybersecurity
Everything filed under AI alignment
AI alignment
Everything filed under AI agents
AI agents
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: In the near term, more capable models should mean safer models. In the near term, more capable models should mean safer models. Last stated yesterday
13 Sept 2026
FC
François Chollet — holds since 2026-09-13 — 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 yesterday
13 Sept 2026
FC
François Chollet — holds since 2026-09-13 — tap for who they are
Same subject: Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. — tap to centre the map on it Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. Last stated 2 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: The near-term goal should be a state of the world that can steer itself towards good outcomes, not any particular end state. — tap to centre the map on it The near-term goal should be a state of the world that can steer itself towards good outcomes, not any particular end state. Last stated a year ago
3 Aug 2025
WM
William MacAskill — holds since 2025-08-03 — tap for who they are
Same subject: The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it. — tap to centre the map on it The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it. Last stated 4 weeks ago
18 Aug 2026
MK
Michael Kratsios — holds since 2026-08-18 — tap for who they are
Same subject: A model that looks smarter and better-behaved while getting better at hiding unwanted actions is the scary combination for AI safety. — tap to centre the map on it A model that looks smarter and better-behaved while getting better at hiding unwanted actions is the scary combination for AI safety. Last stated 5 days ago
9 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-09 — tap for who they are
Same subject: The workable model right now is one super agent for a whole company, not a personal agent for every person. — tap to centre the map on it The workable model right now is one super agent for a whole company, not a personal agent for every person. Last stated 4 months ago
24 May 2026
DS
Dan Shipper — holds since 2026-05-24 — tap for who they are
Same subject: Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public. — tap to centre the map on it Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public. Last stated 3 years ago
29 Aug 2023
AC
Ajeya Cotra — holds since 2023-08-29 — tap for who they are
Same subject: A model is better thought of as a living creature with a personality you must get to know than as a component you specify. — tap to centre the map on it A model is better thought of as a living creature with a personality you must get to know than as a component you specify. Last stated 2 months ago
27 Jul 2026
BC
Boris Cherny — holds since 2026-07-27 — tap for who they are
Same subject: A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. — tap to centre the map on it A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel. Last stated a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — 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 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — 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 a month ago
3 Aug 2026
DD
Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. Last stated 3 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — 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 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. — tap to centre the map on it A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. Last stated 3 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: Access to large-scale generalist AI systems that could be weaponized should be limited, meaning their code and neural network parameters should not be released open-source. — tap to centre the map on it Access to large-scale generalist AI systems that could be weaponized should be limited, meaning their code and neural network parameters should not be released open-source. Last stated 3 years ago
24 Jun 2023
YB
Yoshua Bengio — holds since 2023-06-24 — tap for who they are
Same subject: An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job. — tap to centre the map on it An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job. Last stated 6 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. — tap to centre the map on it Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
At the centre
In the near term, more capable models should mean safer models.
Holds Read this korrent →
Current models are unsafe because they are not smart enough, not because they are too smart.
Holds
Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving.
Holds JD Jeff Dean
The near-term goal should be a state of the world that can steer itself towards good outcomes, not any particular end state.
Holds WM William MacAskill
The tradeoff in cyber-capable models cannot be designed away: the model that can do something nefarious is the same model that hardens the system against it.
Holds MK Michael Kratsios
A model that looks smarter and better-behaved while getting better at hiding unwanted actions is the scary combination for AI safety.
Holds ZM Zvi Mowshowitz
The workable model right now is one super agent for a whole company, not a personal agent for every person.
Holds DS Dan Shipper
Underestimating near-term AI progress is itself a danger, which is why researchers should register their forecasts in public.
Holds AC Ajeya Cotra
A model is better thought of as a living creature with a personality you must get to know than as a component you specify.
Holds
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Holds DD Dmitri Dolgov
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Building a realistic simulator is exactly as hard as building the agent, because the simulator is itself a large AI model.
Holds DD Dmitri Dolgov
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds NB Noam Brown
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 DP Dylan Patel
A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget.
Holds NB Noam Brown
Access to large-scale generalist AI systems that could be weaponized should be limited, meaning their code and neural network parameters should not be released open-source.
Holds
An agent can understand a maximally simplified explanation and still be unable to come up with it — that gap is what is left of the expert's job.
Holds
Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind.
Holds DH Demis Hassabis