Peering into the Home w/ Aerial.ai's Wifi Motion Analytics - TWiML Talk #107

Peering into the Home w/ Aerial.ai's Wifi Motion Analytics - TWiML Talk #107

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. 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. 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 at twimlai.com/ainy2018. Early price ends February 2! The notes for this show can be found at twimlai.com/talk/107. For complete contest details, visit twimlai.com/myaicontest. For complete series details, visit twimlai.com/aiathome.

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100x Improvements in Deep Learning Performance with Sparsity, w/ Subutai Ahmad - #562

100x Improvements in Deep Learning Performance with Sparsity, w/ Subutai Ahmad - #562

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Scaling BERT and GPT for Financial Services with Jennifer Glore - #561

Today we’re joined by Jennifer Glore, VP of customer engineering at SambaNova Systems. In our conversation with Jennifer, we discuss how, and why, Sambanova, who is primarily focused on building hardw...

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Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560

Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560

Today we’re joined by Kamyar Azizzadenesheli, an assistant professor at Purdue University, to close out our AI Rewind 2021 series! In this conversation, we focused on all things deep reinforcement lea...

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Deep Reinforcement Learning at the Edge of the Statistical Precipice with Rishabh Agarwal - #559

Deep Reinforcement Learning at the Edge of the Statistical Precipice with Rishabh Agarwal - #559

Today we’re joined by Rishabh Agarwal, a research scientist at Google Brain in Montreal. In our conversation with Rishabh, we discuss his recent paper Deep Reinforcement Learning at the Edge of the St...

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Designing New Energy Materials with Machine Learning with Rafael Gomez-Bombarelli - #558

Designing New Energy Materials with Machine Learning with Rafael Gomez-Bombarelli - #558

Today we’re joined by Rafael Gomez-Bombarelli, an assistant professor in the department of material science and engineering at MIT. In our conversation with Rafa, we explore his goal of ​​fusing machi...

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Differentiable Programming for Oceanography with Patrick Heimbach - #557

Differentiable Programming for Oceanography with Patrick Heimbach - #557

Today we’re joined by Patrick Heimbach, a professor at the University of Texas working at the intersection of ML and oceanography. In our conversation with Patrick, we explore some of the challenges o...

31 Tammi 202234min

Trends in Machine Learning & Deep Learning with Zachary Lipton - #556

Trends in Machine Learning & Deep Learning with Zachary Lipton - #556

Today we continue our AI Rewind 2021 series joined by a friend of the show, assistant professor at Carnegie Mellon University, and AI Rewind veteran, Zack Lipton! In our conversation with Zack, we tou...

27 Tammi 20221h 8min

Solving the Cocktail Party Problem with Machine Learning, w/ ‪Jonathan Le Roux - #555

Solving the Cocktail Party Problem with Machine Learning, w/ ‪Jonathan Le Roux - #555

Today we’re joined by Jonathan Le Roux, a senior principal research scientist at Mitsubishi Electric Research Laboratories (MERL). At MERL, Jonathan and his team are focused on using machine learning ...

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