According to AndrewYNg on X, DeepLearning.AI launched a new course, Efficient Inference with SGLang: Text and Image Generation, created with LMSys and RadixArk and taught by Richard Chen of RadixArk. As reported by AndrewYNg, the course targets production LLM cost bottlenecks and latency using SGLang techniques such as kernel fusion, paged attention, continuous batching, and optimized KV cache management for both text and image generation. According to AndrewYNg, the curriculum emphasizes practical deployment patterns for serving large models at scale, highlighting business value through reduced GPU hours, higher throughput per dollar, and improved tail latency—key metrics for inference economics.