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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

Aug 31, 2020

Today we’re joined by Gary Ren, a machine learning engineer for the logistics team at DoorDash. 

In our conversation, we explore how machine learning powers the entire logistics ecosystem. We discuss the stages of their “marketplace,” and how using ML for optimized route planning and matching affects consumers,...

Aug 27, 2020

Today we’re joined by Dillon Erb, Co-founder & CEO of Paperspace.

We’ve followed Paperspace since their origins offering GPU-enabled compute resources to data scientists and machine learning developers, to the release of their Jupyter-based Gradient service. Our conversation with Dillon centered on the challenges...

Aug 24, 2020

Today we’re joined by Professor of Computer Science at UC Berkeley, Dawn Song. Dawn’s research is centered at the intersection of AI, deep learning, security, and privacy. She’s currently focused on bringing these disciplines together with her startup, Oasis Labs. 

In our conversation, we explore their goals of...

Aug 20, 2020

Today we’re joined by Wilka Carvalho, a PhD student at the University of Michigan, Ann Arbor.

We first met Wilka at the Black in AI workshop at last year’s NeurIPS conference, and finally got a chance to catch up about his latest research, ‘ROMA: A Relational, Object-Model Learning Agent for...

Aug 17, 2020

Today we’re bringing you the latest TWIML Discussion Series panel on Model Explainability. The use of machine learning in business, government, and other settings that require users to understand the model’s predictions has exploded in recent years. This growth, combined with the increased popularity of opaque ML...