MLOps in the Age of Foundation Models. Evolving Infrastructure for LLMs and Beyond
The field of machine learning has undergone a seismic shift with the rise of large-scale foundation models. From giant language models like GPT-4 to image diffusion models like Stable Diffusion, these powerful models have fundamentally changed how we build and operate ML systems.
In this post, I'll explore how ML infrastructure and MLOps practices have evolved to support foundation models. We'll contrast the "classic" era of MLOps with modern paradigms, examine what's changed, and look at the new patterns and workflows that have emerged. Think of it as upgrading from a standard toolbox to a fully automated factory—the principles are similar, but the scale and complexity are on a different level.