An AI stack: from scaling AI workloads to evaluating LLMs

Hilary Term 2026 Strachey Lecture with Professor Ion Stoica, An AI stack: from scaling AI workloads to evaluating LLMs Large language models (LLMs) have taken the world by storm, enabling new applications, intensifying GPU shortages, and raising
concerns about the accuracy of their outputs. In this talk, I will present several projects I have worked on to address these
challenges. Specifically, I will focus on Ray, a distributed framework for scaling AI workloads, vLLM and SGLang, two
high-throughput inference engines for LLMs, and LMArena, a platform for accurate LLM benchmarking. I will conclude with key
lessons learned and outline directions for future research.