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How much information is in a photograph?
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The automation of mathematics has been going on for more than a century.
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No-one knows when AI will begin having transformative impacts upon the world.
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Contrary to my earlier hypothesis, AI agents probably don't have a constant hazard rate / half-life.
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There is an extremely important question about the near-future of AI that almost no-one is asking.
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The current era of improving AI capabilities using Reinforcement Learning (from verifiable rewards) involves two key types of scaling: Scaling the amount of compute used for RL during training Scaling the amount of compute used for inference during deploy…
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In the last year or two, the most important trend in modern AI came to an end.
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The new scaling paradigm for AI reduces the amount of information a model can learn from per hour of training by a factor of 1,000 to 1,000,000.
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Building on the recent empirical work of Kwa et al. (2025), I show that within their suite of research-engineering tasks the performance of AI agents on longer-duration tasks can be explained by an extremely simple mathematical model — a constant rate of…
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The shift from scaling up the pre-training compute of AI systems to scaling up their inference compute may have profound effects on AI governance.
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Improving model performance by scaling up inference compute is the next big thing in frontier AI.
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AI capabilities have improved remarkably quickly, fuelled by the explosive scale-up of resources being used to train the leading models.
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In the years since I wrote The Precipice, the question I’m asked most is how the risks have changed.
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(PDF available) I show how a standard argument for advancing progress is extremely sensitive to how humanity’s story eventually ends.
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The choice of discount rate is crucially important when comparing options that could affect our entire future.
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Work towards reducing existential risk is likely to happen over a timescale of decades.
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Imagine if we could somehow show the people of the eighteenth century a simple child’s toy from today — say, a speaking doll.
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A eulogy for Peter Eckersley Delivered at his official memorial service Internet Archive, San Francisco, 4 March 2023 Twenty-six years ago, I sat down in an underground room at Melbourne University.
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What is the chance your vote changes the outcome of an election?