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Andrew Ng announced on 2026-04-09 a deeplearning.ai short course titled…
Brief
Andrew Ng announced on 2026-04-09 a deeplearning.ai short course, Efficient Inference with SGLang: Text and Image Generation, built with LMSys and RadixArk and taught by Richard Chen (RadixArk). The course teaches SGLang’s caching to eliminate redundant LLM computation (e.g., ten users’ shared system prompt is processed once), covering KV caches, RadixAttention scaling, and diffusion multi-GPU acceleration.
Why it matters
Andrew Ng announced on 2026-04-09 a deeplearning.ai short course titled "Efficient Inference with SGLang: Text and Image Generation," built in partnership with LMSys and RadixArk and taught by Richard Chen (Member of Technical Staff, RadixArk).
Key details
- SGLang reduces redundant LLM computation by caching and reusing work across requests; for example, when ten users share the same system prompt SGLang processes it once rather than ten times, yielding compounding speedups when contexts overlap.
- The course covers building a KV cache from scratch, scaling cross-user/request caching using RadixAttention, and accelerating diffusion-based image generation with SGLang’s caching plus multi-GPU parallelism.