17 connected korrents · 18 moments from 24 Feb 2018 to 23 Sept 2026.
At the centre
The rush to AI seems to be repeating the web's pathologies: devaluing workers and creators, closed standards, overheated marketing and concentrated power.
Last stated 4 Dec 2025 · 10 months ago
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James Gleick
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Similar wording
People are eager to optimize and put AI in even more places due to the zeitgeist that AI is too expensive and slow.
Last stated 18 Sept 2026 · 2 weeks ago
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Guillermo Rauch
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Similar wording
The web is being flooded with coherent, generic, generated text that buries the writing worth reading.
Last stated 27 Mar 2026 · 6 months ago
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Molly White
Maggie Appleton
Anil Dash
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Similar wording
AI did not create the bottlenecks in software delivery; it threw gas on processes everybody already knew were weak.
Last stated 22 Mar 2026 · 6 months ago
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Nicole Forsgren
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Similar wording
Even with human-like learners, competition will split the AI market into specialised niches rather than hand it to one company.
Last stated 25 Nov 2025 · 10 months ago
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Ilya Sutskever
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Similar wording
The real danger in AI-driven growth is geographic: 50% growth in and around Silicon Valley and business as usual everywhere else.
Last stated 13 Feb 2026 · 8 months ago
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Dario Amodei
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AI marketed as a pure augmenting 'tool' will end up automating jobs anyway, since firms control how it's used.
Last stated 13 May 2026 · 5 months ago
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Jasmine Sun
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Similar wording
Technologies are almost always preceded by slightly worse versions of themselves, and there is no reason for AI to be the exception.
Last stated 24 Feb 2018 · 9 years ago
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Paul Christiano
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Similar wording
There is no AI bubble on the demand side: the shortage of computing capacity is global, and spans every company and industry.
Last stated 8 Jan 2026 · 9 months ago
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Jensen Huang
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Same subject: AI alignment
A control evaluation that reports under one per cent risk should be read as several per cent, because the evaluation can itself fail.
Last stated 7 May 2024 · 2 years ago
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Buck Shlegeris
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Same subject: AI alignment
A deep theoretical understanding to predict AI behavior is unattainable.
Last stated 23 Sept 2026 · a week ago
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Tyler Cowen
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Same subject: AI alignment
A feedback loop that reinforces a behavior pulls it toward whatever improves the loop's own score.
Last stated 26 Aug 2026 · a month ago
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Henrik Karlsson
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Same subject: OpenAI
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Last stated 18 Mar 2024 · 3 years ago
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Sam Altman
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Same subject: OpenAI
A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it.
Last stated 3 Sept 2026 · 4 weeks ago
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Zvi Mowshowitz
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Same subject: OpenAI
Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers.
Last stated 18 Mar 2024 · 3 years ago
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Sam Altman
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Same subject: scaling laws
"Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next.
Last stated 25 Nov 2025 · 10 months ago
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Ilya Sutskever
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Same subject: scaling laws
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 26 Jun 2026 · 3 months ago
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Noam Brown
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Same subject: scaling laws
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 13 Mar 2026 · 7 months ago
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Dylan Patel