In this episode I’m joined by Michel Allegue and Negar Ghourchian of Aerial.ai. Aerial is doing some really interesting things in the home automation space, by using wifi signal statistics to identify and understand what’s happening in our homes and office environments.
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Michel, the CTO, describes some of the capabilities of their platform, including its ability to detect not only people and pets within the home, but surprising characteristics like breathing rates and patterns. He also gives us a look into the data collection process, including the types of data needed, how they obtain it, and how it is parsed. Negar, a senior data scientist with Aerial, describes the types of models used, including semi-supervised, unsupervised and signal processing based models, and how they’ve scaled their platform, and provides us with some real-world use cases.
Enter Our #MyAI Contest!
In this week’s interviews, our AI in Consumer Electronics series, you’ll hear from some great people who help me explore some of the very cool ways that machine learning and AI are being used to enhance our everyday lives.
A few of these companies have provided us with products to give away, and we’re excited to launch the #MyAI contest. To enter, we want to hear from YOU, about the role AI is playing in your home and your personal life, your favorite example of home/personal AI, and/or where you see it all going. So, fire up your webcam or smartphone camera, and get ready to tell us your story!
We’ll post the videos to Youtube and the video with the most likes wins their choice of great prizes including an Anki Cozmo, a Lighthouse smart home camera, or a Google Home Mini! (First prize gets first pick, second prize gets second pick, etc.) Submissions will be open through Feb 11th, and voting will remain open through Feb 18th.
Thanks to our sponsor!
I’d like to thank our friends at Intel AI for their continued support of the podcast. Intel was extremely active at this year’s CES, with a bunch of AI, autonomous driving and VR related announcements. One of the more interesting partnerships announced was a collaboration with the Ferrari Challenge North America race series. Along with the folks at Ferrari Challenge, Intel AI aspires to make the racing viewing experience more personalized by using deep computer vision to detect and monitor individual race cars via camera feeds, and allowing viewers choose the specific car’s feeds that they’d like to watch. Look for my conversation with Intel’s Andy Keller and Emile Chin-Dickey, episode 104 in this series, for an in-depth discussion about this project, and be sure to visit ai.intel.com where you’ll find Andy’s technical blog post on the topic!
And of course, be sure to check out some of the great names that will be at the AI Conference in New York, Apr 29–May 2, where you’ll join the leading minds in AI, Peter Norvig, George Church, Olga Russakovsky, Manuela Veloso, and Zoubin Ghahramani. Explore AI’s latest developments, separate what’s hype and what’s really game-changing, and learn how to apply AI in your organization right now. Save 20% on most passes with discount code PCTWIML. Early price ends February 2!
Mentioned in the Interview
- Enter the #MyAI Contest Now!!
- Real-Time Indoor Localization in Smart Homes Using Semi-Supervised Learning
- Register for the Artificial Intelligence Conference here!
- Check out @ShirinGlander’s Great TWIML Sketches!
- Intel AI
- TWIML Presents: AI in Consumer Electronics
- TWIML Events Page
- TWIML Meetup
- TWIML Newsletter
“More On That Later” by Lee Rosevere licensed under CC By 4.0