This week I spoke with Tristan Zajonc, the CEO and cofounder of Continual, a company that provides an AI layer for enterprise companies or, as we'll get into in the podcast, the so-called 'modern data stack'.
He previously worked at Cloudera as a CTO for machine learning and as the head of the data science platform there, and he holds a PhD in public policy from Harvard University.
In our conversation we discussed the different levels of abstraction one can take when dealing with the MLOps problem. We spoke about all the different ways that machine learning can fail in production settings and of course we discussed the concept of the 'modern data stack' and what that means.
- Tristan Zajonc (@tristanzajonc) / Twitter
- Tristan Zajonc | LinkedIn
- Continual | AI/ML for Your Cloud Data Warehouse
- Company | Continual - Operational AI for the Enterprise
- The Modern Data Stack Ecosystem - Fall 2021 Edition
- The Future of the Modern Data Stack
- Introducing Continual – the missing AI layer for the modern data stack
- Cloudera | The Hybrid Data Cloud Company
- Tristan Zajonc, Sense Platform // Data Driven #28 // June 2014 (Hosted by FirstMark Capital) - YouTube
- Sense Preview - YouTube
- DC_THURS on Operational AI for the Modern Data Stack w/ Tristan Zajonc (Continual) - YouTube
- Enterprise Machine Learning on K8s: Lessons Learned and the Road... - Timothy Chen & Tristan Zajonc - YouTube