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Jeff Boudier
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jeffboudier
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AI for Scientific Discovery Won't Work Without Fixing How We Collaborate. My co-author @cgeorgiaw and I just published a paper challenging a core assumption: that the main barriers to AI in science are technical. They're not. They're social. Key findings: ๐จ The "AI Scientist" myth delays progress: Waiting for AGI devalues human expertise and obscures science's real purpose: cultivating understanding, not just outputs. ๐ Wrong incentives: Datasets have 100x longer impact than models, yet data curation is undervalued. โ ๏ธ Broken collaboration: Domain scientists want understanding. ML researchers optimize performance. Without shared language, projects fail. ๐ Fragmentation costs years: Harmonizing just 9 cancer files took 329 hours. Why this matters: Upstream bottlenecks like efficient PDE solvers could accelerate discovery across multiple sciences. CASP mobilized a community around protein structure, enabling AlphaFold. We need this for dozens of challenges. Thus, we're launching Hugging Science! A global community addressing these barriers through collaborative challenges, open toolkits, education, and community-owned infrastructure. Please find all the links below! Paper: https://huggingface.co/papers/2509.06580 Join: https://huggingface.co/hugging-science Discord: https://discord.com/invite/VYkdEVjJ5J
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VibeGame: Exploring Vibe Coding Games
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