Strachey Lecture: An AI stack: from scaling AI workloads to evaluating LLMs
Автор: CompSciOxford
Загружено: 2026-02-27
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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.
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