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  1. GitHub Blog · AI & ML62

    GitHub extends push protection to unstructured secrets with a ModernBERT classifier built with Microsoft Applied Sciences

    GitHub built a fine-tuned ModernBERT classifier with Microsoft Applied Sciences that assesses candidate secrets in context in under two milliseconds.

    Why it matters: GitHub's nine quarters of push data and the latency budget behind its new secret classifier show how prevention is being moved into the push path.

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  1. Google DeepMind71

    Google DeepMind introduces SynthID Bio for watermarking AI-generated proteins

    Google DeepMind introduced SynthID Bio, a family of watermarking methods that embeds a verifiable signature into AI-generated biological code while preserving protein function in laboratory testing. In wet-lab tests across VEGF-A, the SARS-CoV-2 spike protein RBD and PD-L1, watermarked binder designs matched the hit rate, binding affinity and natural sequence diversity of unwatermarked versions, and for protein folding the method fine-tunes part of AlphaFold 3's diffusion network so predicted 3D coordinates carry a detectable signature. DeepMind is publishing the methods paper and open-sourcing the code, in vitro data and model weights, and says key challenges include making the watermark more robust against deliberate tampering.

    Why it matters: The post details how a watermark is embedded into protein sequences and structures and what wet-lab tests showed about function.

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