The Use Cases of Machine Learning in the Cloud

In this episode of ACM ByteCast, Bruke Kifle hosts Matei Zaharia, computer scientist, educator, and creator of Apache Spark. Matei is the Chief Technologist and Co-Founder of Databricks and an Assistant Professor of Computer Science at Stanford. He started the Apache Spark project during his PhD at UC Berkeley in 2009 and has worked broadly on other widely used data and machine learning software, including MLflow, Delta Lake, and Apache Mesos. Matei's research was recognized through the 2014 ACM Doctoral Dissertation Award, an NSF Career Award, and the US Presidential Early Career Award for Scientists and Engineers.

Matei, who was born in Romania and grew up mostly in Canada, describes how he developed Spark, a framework for writing programs that run on a large cluster of nodes and process data in parallel, and how this led him to co-found Databricks around this technology. Matei and Bruke also discuss the new paradigm shift from traditional data warehouses to data lakes, as well as his work on MLflow, an open-source platform for managing the end-to-end machine learning lifecycle. He highlights some recent announcements in the field of AI and machine learning and shares observations from teaching and conducting research at Stanford, including an important current gap in computing education.