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@yudapearl
Student of causal inference, human reasoning, and history of ideas, all viewed through the sharp lens of artificial intelligence.
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In quotes shared by a user, Affleck says visual-effects work familiarized him with machine learning and GPUs.
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A user suggests the name to emphasize that understanding entails more than Layer-1 and/or Layer-2.
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A user cites Wilfred McClay’s view that Jerusalem contributes faith, narrative and moral guidance where Athens does not.
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A user describes a narrative as a counterfactual concept with a calculus and links to a paper.
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The researcher says many judge a field's impact by how many others acknowledge its influence, rather than by funding.
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A user said something looked like a first-edition cover and that the second edition should be out soon.
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A post announcing the date describes the book as spreading ideas about causal AI.
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A post shares a video of the “Judea, AI, and the Future” panel and describes Horvitz's remarks as a look back at how probabilistic reasoning won its “right place” in AI 42 years ago.
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A user recommends the symposium video, describing it as a journey from classical to modern causal AI in the age of LLMs and reinforcement learning.
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A keynote speaker at Pepperdine’s Symposium on Human-Centered AI said they hoped to persuade the audience that coexistence among diverse beliefs is superior to uniformity in evolutionary and computational terms.
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A user defends Gemini’s verdict by citing their own familiarity with logical rigor in the philosophy of science.
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Judea Pearl shared a video of his Caltech talk addressing that question.
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An organizer says the September 6 gathering included talks by Chris Hitchcock and Daphne Koller, plus a panel and personal reflections from Pearl’s students, collaborators and friends.
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Speaker @yudapearl says a 9:45 a.m. talk on Friday, September 25, will span causality, world models, interfaith relations, identity and coexistence.
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A post quips that image generation belongs in the “transformer hole.”
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A post shares four links to causal-inference papers, describing a swelling “harvest” of research as Congress considers regulating AI research.
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Judea Pearl says the update will include reader-suggested corrections, recent breakthroughs in causal inference, and discussions of large language models and “world models.”
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@yudapearl says the update will cover recent causal-inference breakthroughs, the field’s role in the era of large language models and lessons for “world models.”
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A post calls for a concrete demonstration, with the input, assumptions, data and query made explicit.
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A post questions the idea that cause-and-effect reasoning is a weakness for AI.
