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Hugging Face and Partners Announce Project ProtoStar for AI-Ready Public Science

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Hugging Face and partner organizations announced Project ProtoStar, an initiative aimed at making publicly funded scientific datasets, models, and code more accessible and reusable for AI-driven research. The effort combines open infrastructure, publishing guidance, institutional commitments, and open challenges to explore scientific reuse. Its first challenge, hosted by Carnegie Mellon University on November 2–13, 2026, will ask participants to use historical weather data from 210 U.S. cities to predict climate indicators. Predictions will be compared with observed conditions and simple statistical baselines to test whether AI can improve predictions of urban climate conditions.

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Latest development10/29 08:00 (UTC+8)
Hugging Face and Partners Announce Project ProtoStar to Make Publicly Funded Science AI-ReadyHugging Face Blog

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10/29
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    Hugging Face and Partners Announce Project ProtoStar to Make Publicly Funded Science AI-Ready

    Hugging Face and partner organizations announced Project ProtoStar to make publicly funded scientific datasets, models, and code more accessible and reusable in AI-ready formats. The initiative combines open infrastructure, publishing guidance, and institutional commitments with open challenges exploring scientific reuse. Its first challenge, hosted by Carnegie Mellon University on November 2–13, 2026, asks participants to use historical weather data from 210 U.S. cities to predict climate indicators, with performance compared against observed conditions and simple statistical baselines.

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