In this episode of our AI Platforms series, we're joined by Daniel Jeavons, General Manager of Data Science at Shell. In our conversation, Daniel and I explore the evolution of analytics and data science at Shell, and cover a ton of interesting machine learning use cases that the company is pursuing, such as well drilling and charging smart cars. A good bit of our conversation centers around IoT-related applications and issues, such as inference at the edge, federated machine learning, and digital twins, all key considerations for the way they apply ML. We also talk about the data science process at Shell and the importance of platform technologies to Daniel's organization and the company as a whole and we discuss some of the technologies he and his team are excited about introducing to the company. As many of you know, part of my work involves understanding the way large companies are adopting machine learning, deep learning and AI.