使用 Substra 打造保護隱私的 AI 模型：Owkin 與 Hugging Face 的聯手實踐
Original: Creating Privacy Preserving AI with Substra
As artificial intelligence advances rapidly, data privacy and regulatory compliance (such as GDPR) have become one of the greatest…
Owkin 開源的聯邦學習框架 Substra 已託管於 LF AI & Data 基金會。該框架允許開發者在分散且不公開的數據集上協同訓練 AI 模型，特別適合醫療等高隱私需求領域。本文介紹如何結合 Substra 與 Hugging Face 生態系，實現可追溯、安全且合規的隱私保護機器學習。
As artificial intelligence advances rapidly, data privacy and regulatory compliance (such as GDPR) have become one of the greatest challenges for enterprises and research institutions — especially in sensitive fields like healthcare and finance. To enable collaborative model training without exposing raw data, Substra was developed: an open-source federated learning framework built by Owkin and hosted under the Linux Foundation's LF AI & Data initiative.
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