Definition
Open source / open weights
Models you can download, run, and keep, with no provider able to revoke access.
From the episode “40,000 Models, One API Key, and a $25M Bet on Open Source”Hear it on the podcast1 episode
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Related terms in AI Fundamentals
NondeterministicAI that can produce different outputs for the same input, which is exactly why it is kept away from final claim decisions.OCR (Optical Character Recognition)Technology that converts images of text, including handwritten annotations, into machine-readable text. Critical for legal work, where documents often include handwritten notes and stamped modifications.On-Device AIModel inference that runs locally on your phone instead of sending data to a cloud server. Savva supports airplane mode verification so users can confirm queries never leave the device.Open sourceSoftware whose source code is freely available for anyone to view, use, modify, and share.Open source modelsAn AI model whose weights, code, and details of its training data are released so anyone can run, inspect, modify, and build on it.Open weights and open source modelsModels whose parameters are published, so anyone can run and fine-tune them in their own environment.Open-Source LLM StrategyThe decision to release AI model weights and architecture publicly, enabling community contribution, local deployment, trust verification, and developer adoption at scale. China's approach: all major LLMs released open source. US approach (except Meta): all major frontier models remain closed. Open source compounds via the scientific method — thousands of contributors find flaws, optimize, build smaller deployment-specific variants, and expand use cases. The strategic argument: whoever wins developer adoption wins the long-term market, and open source is how you build with developers rather than selling to them.Open-weight modelA model whose trained weights are publicly downloadable, even if its training data and code are not.