Stanford CS336 Lecture 10: Percy Liang on Speculative Decoding and Quantization
techNmak · x · 2026-10-17
Entry 3 in an LLM inference learning list: Lecture 10 (Inference) of Stanford CS336: Language Modeling from Scratch, 2025, taught by Percy Liang. It covers memory bottlenecks, quantization, speculative decoding, and PagedAttention. The full course walks through building an LLM end to end — data, architecture, training, and deployment — with all materials public.
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