Marrying Physics-Based and Data Driven ML Models with Josh Bloom

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

Recently I had a chance to catch up with a friend and friend of the show, Josh Bloom, vice president of data & analytics at GE Digital. If you’ve been listening for a while, you already know that Josh was on the show around this time last year, just prior to the acquisition of his company by GE Digital.

It was great to catch up with Josh on his journey within GE, and the work his team is doing around Industrial AI, now that they’re part of the one of the world’s biggest industrial companies. We talk about some really interesting things in this show, including how his team is using autoencoders to create training datasets, and how they incorporate knowledge of physics and physical systems into their machine learning models.

500 Thousand Reasons for Celebration!

If you get my newsletter you already know this, but last week, we hit a MAJOR milestone for the podcast. I’m excited to share that, thanks to you, we’ve served up over 500 thousand plays of this show! We’re super grateful to everyone who’s ever listened to the show, sent us feedback, or engaged with us via the site or social media ! Thanks also to all our guests, especially those who started as listeners and later became guests, like Evan Wright and Sharath Rao. We’ve come a long way, in a short amount of time, and we couldn’t have done any of it without any of you.

TWIML Online Meetup Update

We are less than a week away from the first ever meeting of our online paper reading group, the TWIML Meetup. Our first discussion will be on the recent paper from Apple, “Learning from Simulated and Unsupervised Images through Adversarial Training.” If you haven’t registered yet, head over to and register. The meetup is Wednesday August 16, at 11 am Pacific Time. It will be recorded for those who can’t participate live. If you’ve already registered, but haven’t read the paper yet, now’s the time to get started. If you have started reading, and have questions, please post them over on the meetup’s Slack channel, which you should have been invited to after registering.

Thanks to Our Sponsors

Bonsai Logo If you’re trying to build AI-powered applications focused on optimizing and controlling the physical systems in your enterprise, whether robots or HVAC systems or vehicle fleets, you should take a look at what Bonsai up to. They’ve got a unique approach to building AI models that lets you model the real-world concepts in your application; automatically generate, train and evaluate low level models for your project–using technologies like reinforcement learning; and easily integrate those models into your applications and systems using APIs. You can check them out at, and definitely let them know you appreciate their support of the podcast.

I’m also excited to announce and GE Digital as a sponsor. was among the first companies I began following in what I called the Machine Learning platforms space, back in 2012/2013. I’ve since interviewed co-founder Josh Bloom here on the show and mentioned the company’s subsequent acquisition by GE Digital. At GE Digital, the team is focused on creating technology and solutions to enable advanced capabilities for the Industrial Internet of things, making infrastructure more intelligent and advancing the industries critical to the world we live in. I want to give a hearty thanks and shout-out to the team at and GE Digital for supporting my Industrial AI research and this podcast series. Of course you can check them out at

Contest Update

We’re ready to announce the first winner for our AI Conference Giveaway! Congratulations to Xinyu, student at Yale University! Xinyu was one of only 5 people to complete every possible method of entry, and clearly it paid off! Xinyu, we look forward to seeing you in SF! Our second winner is Richard, incoming student at the University of Cambridge! Richard we also look forward to having you as one of our guests of the conference! If you weren’t one of the lucky winners, but are still interested in attending The AI Conference, register using the code PCTWIML for 20% off registration! Links to the conference can be found below!

About Josh

Mentioned in the Interview

1 comment
  • Hank Roark

    Josh mentions there are a few papers on using GANs for dealing with sensitive data, allowing the GAN to be passed around with guarantees that the original data will not be produced, but are good enough for building classifier against. Any chance you have a reference to the referenced papers?

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