Strachey Lecture: An AI stack: from scaling AI workloads to evaluating LLMs скачать в хорошем качестве

Strachey Lecture: An AI stack: from scaling AI workloads to evaluating LLMs

Strachey Lecture: An AI stack: from scaling AI workloads to evaluating LLMs Originally uploaded on the University of Oxford Podcast page 26/02/2026 Abstract: 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. The Strachey Lectures are generously supported by OxFORD Asset Management.