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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Data Science on AWS with Chris Fregly and Antje Barth - #490

Data Science on AWS with Chris Fregly and Antje Barth - #490

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Accelerating Distributed AI Applications at Qualcomm with Ziad Asghar - #489

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Buy AND Build for Production Machine Learning with Nir Bar-Lev - #488

Today we’re joined by Nir Bar-Lev, co-founder and CEO of ClearML. In our conversation with Nir, we explore how his view of the wide vs deep machine learning platforms paradox has changed and evolved ...

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Applied AI Research at AWS with Alex Smola - #487

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Today we’re joined by Alex Smola, Vice President and Distinguished Scientist at AWS AI. We had the pleasure to catch up with Alex prior to the upcoming AWS Machine Learning Summit, and we covered a TO...

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Causal Models in Practice at Lyft with Sean Taylor - #486

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Using AI to Map the Human Immune System w/ Jabran Zahid - #485

Using AI to Map the Human Immune System w/ Jabran Zahid - #485

Today we’re joined by Jabran Zahid, a Senior Researcher at Microsoft Research. In our conversation with Jabran, we explore their recent endeavor into the complete mapping of which T-cells bind to whic...

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Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484

Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484

Today we conclude our 2021 ICLR coverage joined by Konstantin Rusch, a PhD Student at ETH Zurich. In our conversation with Konstantin, we explore his recent papers, titled coRNN and uniCORNN respectiv...

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What the Human Brain Can Tell Us About NLP Models with Allyson Ettinger - #483

What the Human Brain Can Tell Us About NLP Models with Allyson Ettinger - #483

Today we continue our ICLR ‘21 series joined by Allyson Ettinger, an Assistant Professor at the University of Chicago.  One of our favorite recurring conversations on the podcast is the two-way street...

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