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  "text": "Yesterday’s PyTorch 2.11 live Q&A with Nikita Shulga and Andrey Talman, moderated by Chris Gottbrath, covered five major focus areas: FlexAttention with FlashAttention-4, differentiable collectives, MPS operator expansion, RNN/LSTM GPU export support, and hardware backend improvements for AMD and Intel.\n\nA key topic of conversation was the influx of AI-generated code contributions and the specific framework maintainers use to protect repository integrity. Watch the clip below to see the discussion.\n\nTechnical Policy on AI Contributions:\n\n1. User owns the code: PyTorch treats the human submitter as the sole owner. Nikita Shulga stated that \"User owns the code, not AI system\" and maintainers will treat the contribution the same regardless of whether it comes through an AI agent or a person.\n\n2. Called actionable: To preserve maintainer bandwidth, Nikita noted that contributions should focus on issues explicitly \"called actionable.\" High-volume bursts, such as \"fifty pull requests in an hour,\" are considered \"disruptive behavior\" and subject to temporary account blocks.\n\n3. Test-driven development: PyTorch values \"test-driven development.\" Nikita Shulga noted that if an AI contribution consists of \"only fix,\" contributors will likely receive a comment to \"please add a regression test\" to verify the change against existing repository test structures.\n\n4. First line of defense: Andrey Talman confirmed that the CI-CD system remains the \"first line of defense,\" finding issues and ensuring code meets stability standards before it is accepted.\n\nFull video: https://t.co/kGiFS5N9RB\n\n#PyTorch #OpenSource #MachineLearning",
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