Debating the Role of Notebooks in Data Science and Machine Learning

Today we’re joined by Dillon Erb, CEO of Paperspace. 

If you’re not familiar with Dillon, he joined us about a year ago to discuss Machine Learning as a Software Engineering Discipline; we strongly encourage you to check out that interview as well. In our conversation, we explore the idea of compositional AI, and if it is the next frontier in a string of recent game-changing machine learning developments. We also discuss a source of constant back and forth in the community around the role of notebooks, and why Paperspace made the choice to pivot towards a more traditional engineering code artifact model after building a popular notebook service. Finally, we talk through their newest release Workflows, an automation and build system for ML applications, which Dillon calls their “most ambitious and comprehensive project yet.”

The complete show notes for this episode can be found at twimlai.com/go/520.