Grounded Research: From Google Brain to MLOps to LLMOps — with Shreya Shankar of UC Berkeley

This podcast episode covers various topics in machine learning development, including the importance of velocity, validation, and versioning; the challenges of bridging the gap between development and production environments; innovative research initiatives at Berkeley; the significance of dynamic data, pre-commits, and versioning in ML development; the challenges of data validation and versioning in ML; integrating large language models into applications; the intersection of MLOps, grounded theory, and large language models; underappreciated research areas in industry; challenges and opportunities presented by AI advancements; and the impact of AI on the field of design systems.