Scalable Distributed Deep Learning with Hillery Hunter

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

This week on the podcast we’re running a series of shows consisting of conversations with some of the impressive speakers from an event called the AI Summit in New York City. The theme of the conference, and the series, is AI in the Enterprise, and I think you’ll find it really interesting in that it includes a mix of both technical and case-study-oriented discussions. My guest for this first show in the series is, Hillery Hunter, IBM Fellow & Director of the Accelerated Cognitive Infrastructure group at IBM’s T.J. Watson Research Center. Hillery and I met a few weeks back in New York and I’m really glad that we were able to get her on the show. Hillery joins us to discuss her team’s research into distributed deep learning, which was recently released as the PowerAI Distributed Deep Learning Communication Library or DDL.

In my conversation with Hillery, we discuss the purpose and technical architecture of the DDL, it’s ability to offer fully synchronous distributed training of deep learning models, the advantages of its Multi-Ring Topology, and much more. This is for sure a nerd alert pod, especially for the performance and hardware geeks among us . Be sure post any feedback or questions you may have to the show notes page, which you’ll find at

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TWIML Online Meetup

The details of our next TWIML Online Meetup have been posted! On Wednesday, December 13th, at 3pm Pacific Time, we will be joined by Bruno Gonçalves, who will be presenting the paper “Understanding Deep Learning Requires Rethinking Generalization”. If you’re already registered for the meetup, you should have already received an invitation with all the details. If you still need to register for the meetup, head over to to do so. We hope to see you there!

About Hillery

Mentioned in the Interview

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