#policy
Wiki 25
- 6 months to live for open models Lambert predicts a US ban or delay on frontier open weights by early 2027, calls Anthropic's distillation campaign regulatory capture, and proposes off-ramps
- A Safe Path to Open Weights Thinking Machines Lab's release framework for open weights - test the model, stage access, filter dangerous knowledge - applied to its Inkling models
- Banning Open Source AI Would Be A Mistake Lambert and Kevin Xu's 2026 op-ed defending open source AI on education, innovation and competition as Washington moves to regulate models
- China's Structural Advantage in Open Source AI Kevin Xu, after Ion Stoica, on why Chinese labs default to open weights - talent, data, academia-industry ties, and shared artifacts
- Chinese Open Source: A Definitive History Kevin Xu traces Chinese open source from Linux in 1994 through Alibaba, Kaiyuanshe, Huawei and the state to the DeepSeek-era AI labs
- Consent in Crisis: The Rapid Decline of the AI Data Commons Longpre et al.'s audit of 14,000 domains behind C4, RefinedWeb and Dolma - AI crawl restrictions surged in 2023-2024, cutting off the best web data
- Detecting and countering misuse of AI: September 2026 Anthropic's threat report on Claude misuse from Dec 2025 to Aug 2026, led by seven Chinese labs said to distill Claude and pass it off as their own models
- From Open Source Software to Open Source Strategy Bill Gurley on open source as a corporate weapon, from Android and Kubernetes to autonomous vehicles and the fight over open-weight AI
- GLM-5.2 is the step change for open agents Nathan Lambert on GLM-5.2 as the first open-weight model that works as a general coding agent, released while Claude Fable 5 was restricted
- How much does distillation really matter for Chinese LLMs? Lambert reads Anthropic's February 2026 disclosure against DeepSeek, Moonshot and MiniMax and argues distillation helps but is not decisive
- Kimi K3: The open-weights escalation Nathan Lambert on Kimi K3 as the first true frontier open-weight model, what it says about Chinese labs, and why banning open weights backfires
- LLM Distillation Training one LLM on another's outputs, from SFT on generated text to on-policy KD, and the 2025-2026 fight over Chinese labs distilling US models
- Nonproliferation is the wrong approach to AI misuse Helen Toner on why fixed dangerous capabilities cannot be kept from bad actors, and why the frontier-to-open lag should be used as an adaptation buffer
- On the Societal Impact of Open Foundation Models Kapoor, Bommasani et al.'s 2024 paper - five properties of open-weight models and a marginal-risk framework showing most misuse studies were incomplete
- Open Source AI is the Path Forward Mark Zuckerberg's July 2024 letter releasing Llama 3.1 405B, arguing open models are better for developers, for Meta, and for safety against China
- Open-Source AI & Open Models Reading List Nathan Lambert's annotated list of the best writing on open models — why they exist, why China leads, the gap, cyber risk and distillation
- PHK's last Bikeshed: the end of FOSS as we know it Poul-Henning Kamp's farewell ACM Queue column — LLM code review is a fad, but age verification, attestation, and EU accountability end BDFL-style FOSS
- Some Simple Economics of Open versus Closed AI Christian Catalini's a16z essay using innovation economics to argue open weights change where AI investment goes and who profits, not how much
- The Arguments Against Open Source AI are Very Bad Tom Bedor's rebuttal to the frontier-lab case against open weights, using encryption export controls as the precedent
- The ATOM Project: American Truly Open Models Nathan Lambert's 2025 memo arguing the US lost open-model leadership to China and needs several 10,000-GPU labs building fully open models
- The distillation panic Lambert argues "distillation attacks" wrongly brands a standard training technique and warns US policy could end up banning Chinese open weights
- The Gradient of Generative AI Release: Methods and Considerations Irene Solaiman's 2023 framework placing AI releases on a six-level gradient from fully closed to fully open, with the tradeoffs and controls at each
- The OpenAI/Huggingface incident; how we should manage the imminent arrival of autonomous hacking too cheap to meter Joshua Saxe reads an unreleased OpenAI model hacking Hugging Face as the start of cheap autonomous hacking, and argues for diffusion over restriction
- US Scrutiny of Chinese Model Use House probes of Airbnb, Cursor and DoorDash over Chinese AI models, set against Western companies moving to Chinese open weights to cut costs
- We urgently need a coherent national AI cybersecurity policy Joshua Saxe's AI Security Forum 2026 keynote - replace capability-threshold launch gates with a national observatory that measures net cyber harm