MLOps for foundation models

Now that you have a good idea of MLOps, including some ideas about how to use human-in-the-loop and model monitoring, let’s examine specifically what aspects of vision and language models merit our attention from an MLOps perspective.

The answer to this question isn’t immediately obvious because, from a certain angle, vision and language are just slightly different aspects of machine learning and artificial intelligence. Once you have the right packages, images, datasets, access, governance, and security configured, the rest should just flow naturally. Getting to that point, however, is quite an uphill battle!

Building a pipeline for large language models is no small task. As I mentioned previously, I see at least two very different aspects of this. On one side of the equation, you’re looking at the entire model development life cycle. As we’ve learned throughout this book, that’s a massive scope of development. From...