#ai-lab

Wiki 8

• 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
• DeepSeek Chinese AI lab whose V3/R1/V4 model line drove the open-weights reasoning-model cost-collapse story of 2024-2026
• 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
• Notes from inside China's AI labs Nathan Lambert's May 2026 trip report from Chinese AI labs - student-heavy teams, less ego, Claude everywhere, in-house data, and too few Nvidia chips
• 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 ATOM Report: Measuring the Open Language Model Ecosystem Lambert and Brand's 2026 adoption study of ~1.5K open models - China passed the US in downloads in mid-2025, Qwen dominates, plus a size-normalized metric
• The Z.ai Playbook ChinaTalk interviews Z.ai's Zixuan Li on GLM - why Zhipu open-sources, the coding plan, role-play and translation, release within hours
• Z.ai (Zhipu AI) Chinese lab behind the open-weight GLM models, from a 2021 Tsinghua paper to GLM-5.3, and how its release practice changed along the way