How to Draw an Owl and Build Effective ML Stacks

apply(conf) - May '22 - 30 minutes

They’re handing us an engine, transmission, breaks, and chassis and asking us to build a fast, safe, and reliable car,” a data scientist at a recently IPO’ed tech company opined, while describing the challenges he faces in delivering ML applications using existing tools and platforms. Although hundreds of new MLOps products have emerged in the past few years, data scientists and ML engineers are still struggling to develop, deploy, and maintain models and systems. In fact, iteration speeds for ML teams may be slowing! In this talk, Sarah Catanzaro, a General Partner at Amplify Partners, will discuss a dominant design for the ML stack, consider why this design inhibits effective model lifecycle management, and identify opportunities to resolve the key challenges that ML practitioners face.

Sarah Cantazaro

General Partner

Amplify Partners

Sarah Catanzaro is a General Partner at Amplify Partners, where she focuses on investing in and advising high potential startups building data and machine learning tools, platforms, and applications. Her investments at Amplify include startups like OctoML, Intervenn Biosciences, RunwayML, and Hex among others. Sarah also has several years of experience defining data strategy and leading data science teams at startups and in the defense/intelligence sector including through roles at Mattermark, Palantir, Cyveillance, and the Center for Advanced Defense Studies.