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  1. The Decoder82

    Former OpenAI researcher says Nvidia Blackwell fingerprints appear in six Chinese AI models

    1-flash. The method exploits the random seed pattern PyTorch uses to initialize weights, which reflects a GPU's core count: 148 cores for B200/B300 and 152 for GB200/GB300, versus 132 for Hopper H100/H800. DePue says he reproduced the results for DeepSeek-V4-Flash and Kimi K3 on real Blackwell chips, published verification code on GitHub, and that the method correctly identified all 24 control models with known hardware.

    Why it matters: A former OpenAI researcher's weight-initialization fingerprint method offers a rare technical window into which Nvidia chips trained six Chinese models, while explicitly stopping short of proving export-law violations.

  1. Anthropic Research65

    Anthropic reports early progress on using Claude to accelerate drug development

    Anthropic's life sciences team has spent several months working with six drug developers, including Bristol Myers Squibb, Generate Biomedicines and Divergence Labs, plus running its own discovery programs, to test where Claude can speed up drug development. Reported early results include a Generate design roughly 70% shorter than the standard version that let immune cells make about 10 times as many receptors, and roughly 35,000 antibody designs generated largely autonomously for Divergence in about a month. Anthropic says the work is still mostly preclinical and plans to extend Claude into clinical trials as the programs advance.

    Why it matters: Anthropic's first detailed account of embedding Claude in real drug programs shows where the model helps and where it still falls short across six partners.

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