This week, I’m happy to bring you my interview with Calvin Seward, a research scientist with Berlin, Germany based Zalando. While our American listeners might not know the name Zalando, they’re one of the largest e-commerce companies in Europe with a focus on fashion and shoes. Calvin is a research scientist there, while also pursuing his doctorate studies at Johannes Kepler University in Linz, Austria.
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Our discussion, which continues our Industrial AI series, focuses on how Calvin’s team tackled an interesting warehouse optimization problem using deep learning. Calvin also gives his thoughts on the distinction between AI and ML, and the four P’s that he focuses on: Prestige, Products, Paper, and Patents.
About the Industrial AI Series
This show is part of our Industrial AI series. I’ve mentioned my interest in industrial applications of machine learning & AI a few times on the podcast. I’ve been doing some research in the area, and I’m very close to publishing a special report on the topic. If you’re interested in learning more about this project, the report, or the podcast series as a whole, check out our Industrial AI page.
Thank everyone who’s taken the time to enter our AI Conference giveaway. We’ve got a couple of exciting updates for those of you who want in on this opportunity. First, we’re making it even easier to enter our ticket giveaway for the San Francisco event! Second, we’re giving away two tickets now, not one! To enter the contest in 30 seconds or less just hit pause now and visit twimlai.com/aisf right from your phone!
Thanks to Our Sponsors
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 bons.ai/twimlai, and definitely let them know you appreciate their support of the podcast.
I’m also excited to announce Wise.io and GE Digital as a sponsor. Wise.io 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 Wise.io 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 Wise.io and GE Digital for supporting my Industrial AI research and this podcast series. Of course you can check them out at Wise.io.