William Benton
William Benton is passionate about making it easier for machine learning practitioners to benefit from advanced infrastructure and making it possible for organizations to manage machine learning systems. His recent roles have included defining product strategy and professional services offerings related to data science and machine learning, leading teams of data scientists and engineers, and contributing to many open source communities related to data, ML, and distributed systems. Will was an early advocate of building machine learning systems on Kubernetes and developed and popularized the “intelligent applications” idiom for machine learning systems in the cloud. He has also conducted research and development related to static program analysis, language runtimes, cluster configuration management, and music technology.
NVIDIA
Session
Many of the putatively novel challenges of building systems around LLMs are analogous to problems we've solved for conventional ML systems. This talk will show you why the things you already know about building ML systems are still relevant for LLM systems — and where the true novelty of LLMs lies.