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@shoyer
AI for physical simulation at @PeriodicLabs, formerly weather/climate @Google and scientific python contributor (Xarray, NumPy, JAX).
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shoyer praised Argon's writing but said it doubled down on what they called a lie.
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A post recommends tackling problems that are fast and easy to verify, removing verification bottlenecks, and gathering data for problems that are hard to check.
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A commenter calls high-fidelity physical simulation "nearly impossible" and argues that most people without experience underestimate its difficulty.
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A user describes a Chrome bookmarks bar filled with variations of “Claude” and tags @ClaudeDevs to ask what’s going on.
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The reply also credits related progress in algorithms, arguing that the world's supply of computing power isn't an independent variable.
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Hiring targets data curation, evaluations, and training tasks to advance AI models for physical sciences.
