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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.

Dec 30, 2020

Today we kick off our annual AI Rewind series joined by friend of the show Pablo Samuel Castro, a Staff Research Software Developer at Google Brain.

Pablo joined us earlier this year for a discussion about Music & AI, and his Geometric Perspective on Reinforcement Learning, as well our RL office hours during the...


Dec 28, 2020

Today we close out our NeurIPS series joined by Aravind Rajeswaran, a PhD Student in machine learning and robotics at the University of Washington.

At NeurIPS, Aravind presented his paper MOReL: Model-Based Offline Reinforcement Learning. In our conversation, we explore model-based reinforcement learning, and if models...


Dec 23, 2020

As we continue our NeurIPS 2020 series, we’re joined by friend-of-the-show Charles Isbell, Dean, John P. Imlay, Jr. Chair, and professor at the Georgia Tech College of Computing.

This year Charles gave an Invited Talk at this year’s conference, You Can’t Escape Hyperparameters and Latent Variables: Machine...


Dec 21, 2020

Today we kick off our NeurIPS 2020 series joined by Taco Cohen, a Machine Learning Researcher at Qualcomm Technologies.

In our conversation with Taco, we discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks,” which explores...


Dec 18, 2020

Today we close out our re:Invent series joined by Edgar Bahilo Rodriguez, Lead Data Scientist in the industrial applications division of Siemens Energy.

Edgar spoke at this year's re:Invent conference about Productionizing R Workloads, and the resurrection of R for machine learning and productionalization. In our...