17 connected korrents · 18 moments from 10 Oct 2023 to 3 Nov 2026.
At the centre
AI increases biosecurity risk at the margin, with how much depending on capability trajectories, biosecurity responses, and governance.
Last stated 16 Sept 2026 · 2 months ago
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Katelyn Jetelina
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Similar wording
AI-caused catastrophic extinction risk is negligible, but disasters like critical-infrastructure cyberattacks and bio-risks from AI are real and worth debating.
Last stated 10 Sept 2026 · 2 months ago
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Nathan Lambert
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Similar wording
AI's biological risk is unlike its cyber risk, because you cannot patch your DNA.
Last stated 8 Sept 2026 · 2 months ago
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Alex Bores
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Similar wording
The risks of AI are growing faster than our will and capacity to contain them.
Last stated 26 Sept 2026 · a month ago
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Ben Rhodes
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Similar wording
AI's societal benefits and risks are determined by how it is deployed, not by how capable the underlying models become.
Last stated 9 Sept 2025 · a year ago
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Arvind Narayanan
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Similar wording
Perhaps the two biggest AI risks, somewhat in tension, are losing control of AI and power becoming too centralized in one company, model or person.
Last stated 23 Aug 2026 · 2 months ago
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Sam Altman
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Similar wording
Cybersecurity risks from advanced AI very likely will not come close to being as bad as either Covid or global warming.
Last stated 1 Sept 2026 · 2 months ago
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Tyler Cowen
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Similar wording
As AI systems become more capable, the danger of false or unverifiable safety claims grows, pushing competing companies toward cutting corners.
Last stated 19 Jun 2025 · a year ago
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Miles Brundage
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Similar wording
Models are becoming superhuman at breaking in and out of computer systems, which widens the scope of AI risk enormously.
Last stated 6 Sept 2026 · 2 months ago
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Jakub Pachocki
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Same subject: AGI
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Last stated 4 Jun 2026 · 5 months ago
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Alex Imas
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Same subject: AGI
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Last stated 7 Jun 2025 · a year ago
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Gary Marcus
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Same subject: AGI
A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality
Last stated 10 Oct 2023 · 3 years ago
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Chip Huyen
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Same subject: AI agents
A codebase is the most important context an AI agent has, and letting many different models add to it without consistent patterns leads to trouble.
Last stated 3 Nov 2026 · 2 days ago
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Derek Briggs
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Same subject: AI agents
A collection of AI agents does not automatically form a functioning organization any more than a group of smart people does.
Last stated 21 May 2026 · 6 months ago
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Rohit Krishnan
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Same subject: AI agents
A company cannot be led by machines, because nobody would have recourse against them.
Last stated 15 Sept 2026 · 2 months ago
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Tobias Lütke
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Same subject: reinforcement learning
A physical AI company needs three AIs, not one — the agent, the simulator and the critic — turning deployment into a flywheel.
Last stated 3 Aug 2026 · 3 months ago
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Dmitri Dolgov
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Same subject: reinforcement learning
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Last stated 17 Nov 2025 · 12 months ago
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Andrej Karpathy
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Same subject: reinforcement learning
AlphaGo showed that for over 2,000 years human minds explored only a small part of the landscape of Go
Last stated 11 Dec 2025 · 11 months ago
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Yuval Noah Harari