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Martin Casado explains AI as a fundamentally new abstraction layer of computing: "I don't think in the history of computer science that I can recall have we ever abdicated actual reasoning or logic. It's always been a resource. It's been like compute, network, and storage..." "And then the human is putting in the high-level thing, and it's using the compute, network, and storage to calculate the answer." "But now I feel like you're actually abdicating thinking in a way, where you're like,…
a16z@a16zAug 25
Your startup intuitions were trained on a world that no longer exists. Steven Sinofsky and Martin Casado have watched computing flip from an engineering-bound field to a capital-bound industry. Twenty people can now put a billion dollars to work productively, AI solves the distribution problem that kept startups small, and challengers sit on a level playing field with Microsoft and Meta for the first time. With Erik Torenberg, they get into why some mathematicians are cheering on their own automation, every AI panic that already happened in past eras of computing, and why nobody can predict the capabilities of a model built with $20 billion. 00:55 Why mathematicians love being automated 02:45 Is AI math worth any money? 08:50 The first proof humans couldn't check 14:35 Computing before electricity 19:50 How IBM explained computers in 1953 26:00 The failed computer that birthed the web 27:50 When Harvard banned computers from exams 30:20 Is AI just another abstraction layer? 38:15 When 20 people can spend $1B productively 42:50 The zero-sum VC myth 46:25 Disruption is physics, not business school 53:25 The chip Intel called a printer part 55:05 What a $20B model can do 59:45 What Martin got wrong about AI risk YouTube: https://www.youtube.com/watch?v=GHPB1MwlKU0 @stevesi @martin_casado @eriktorenberg
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