Fast TPU kernels for linear attention released; team pitches DeepMind on collaboration
gabriberton · x · 2026-10-14
A student of Prof. Joey released impressively fast TPU kernels for modern variants of linear attention. The team says it now just needs TPU access to do actual architecture research and has publicly asked Google DeepMind to collaborate. Gabrielle Berton reposted hoping relevant colleagues see it.
More from Infra
- OpenJet claims Qwen3.8-27B coding runs 1.9x faster than llama.cpp on one RTX 3090 — JeremyCMorgan · 2026-10-23
- Jensen Huang lays out NVIDIA's full Vera Rubin agentic system: NVL72, MGX, CMX and RTX — rohanpaul_ai · 2026-10-23
- Jensen Huang details Vera Rubin agentic stack: NVL72, MGX, CMX and RTX — rohanpaul_ai · 2026-10-23
- ONNX to Transformers.js: running models directly in your browser — JosephJacks_ · 2026-10-23
- MiniMax M3.1 Flash free for 3 days on 0G, with 1M context and 512K output — MiniMax_AI · 2026-10-23
- "We bet on Cloudflare and it paid off": R2 and D1 at billion scale — dinasaur_404 · 2026-10-23