Explore the evolution of Large Language Models and learn efficient scaling and deployment strategies in this insightful conference talk by Hanlin Tang. Discover the advantages of a decentralized approach using multiple specialized models over a single giant AGI model. Understand the benefits of companies training their own custom models, including data privacy considerations. Gain valuable insights into when it's appropriate to build your own models and explore available tools for training and deployment. Presented by the CTO and Co-founder of MosaicML, this 25-minute talk draws from Hanlin's extensive experience in AI research and deployment, offering practical knowledge for professionals interested in advancing their understanding of LLMs in production environments.
Efficiently Scaling and Deploying Large Language Models
Overview
Syllabus
Efficiently Scaling and Deploying LLMs // Hanlin Tang // LLM's in Production Conference
Taught by
MLOps.community
