It is indeed a wonderful time to build machine learning systems, as we don’t have much to do anymore! Thanks to a growing ecosystem of tools and shared best practices, even small teams can be incredibly productive at “reasonable scale”. In this talk, we present our philosophy for modern, no-nonsense data pipelines, highlighting the advantages of a PaaS approach, and showing (with open source code) how the entire toolchain works on real-world data with realistic constraints. We conclude discussing our proposal for self-documenting ML DAGs - 'DAG cards' for Metaflow - and sharing unsolicited advice on the future of MLOps for “reasonable” companies.
Jacopo Tagliabue Bio:
Educated in several acronyms across the globe (UNISR, SFI, MIT), Jacopo Tagliabue was co-founder and CTO of Tooso, an A.I. company in San Francisco acquired by Coveo in 2019. Jacopo is currently the Lead A.I. Scientist at Coveo, shipping models to hundreds of customers and millions of users. When not busy building products, he is exploring topics at the intersection of language, reasoning and learning: his research and industry work is often featured in the general press and premier A.I. venues. In previous lives, he managed to get a Ph.D., do sciency things for a pro basketball team, and simulate a pre-Columbian civilization.
0:00 - Starting soon
2:06 - Presentation
35:02 - Discussion