Beyond MLOps: Building AI systems with Metaflow

Abstract: 

Open-source Metaflow has been powering ML systems at companies like Netflix, 23andMe, and Goldman Sachs for years. With the advent of Generative AI, companies are starting to consider how the new techniques can be embedded in existing applications, and how they can power wholly new product experiences. This requires new engineering and infrastructure, in particular if the company wants to own the models and the user experience, integrating AI tightly into their business and systems, going beyond widely available commercial APIs.

In this talk, we will provide an overview of how Metaflow helps you build novel, differentiated AI-powered systems that require large-scale data engineering, model training, content embedding, inference, and more. We will cover changes compared to earlier ML stacks, focusing on the quickly growing compute needs in particular, and share our recent experiences from real-life large-scale AI use cases, and how they interoperate with existing data and ML systems.

Bio: 

Ville has been developing infrastructure for machine learning for over two decades. He has worked as an ML researcher in academia and as a leader at a number of companies, including Netflix where he led the ML infrastructure team that created Metaflow, a popular open-source framework for data science infrastructure. He is a co-founder and CEO of Outerbounds, a company developing modern human-centric ML. He is also the author of the book Effective Data Science Infrastructure, published by Manning.

Open Data Science

 

 

 

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