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

In this episode I’m joined by Jeff Dean, Google Senior Fellow and head of the company’s deep learning research team Google Brain, who I had a chance to sit down with last week at the Googleplex in Mountain View. As you’ll hear, I was very excited for this interview, because so many of Jeff’s contributions since he started at Google in ‘99 have touched my life and work. In our conversation, Jeff an...

In this episode I’m joined by Lyne Tchapmi, PhD student in the Stanford Computational Vision and Geometry Lab, to discuss her paper, “SEGCloud: Semantic Segmentation of 3D Point Clouds.” SEGCloud is an end-to-end framework that performs 3D point-level segmentation combining the advantages of neural networks, trilinear interpolation and fully connected conditional random fields. In our conversation...

In this episode, I'm joined by Google Research Scientist Ryan Poplin, who recently co-authored the paper “Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.” In our conversation, Ryan details his work training a deep learning model to predict various patient risk factors for heart disease, including some surprising ones like age and gender. We also dive in...

In this episode, i'm joined by Clare Gollnick, CTO of Terbium Labs, to discuss her thoughts on the “reproducibility crisis” currently haunting the scientific landscape. For a little background, a “Nature” survey in 2016 showed that "more than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments." Cl...

In this episode, I’m joined by GK Senthil, director & chief product owner for innovation at Toyota Connected. GK and I spoke about some of the potential opportunities and challenges for smart cars. We discussed Toyota’s recently announced partnership with Amazon to embed Alexa in vehicles, and more generally the approach they’re taking to get connected car technology up to par with smartphones and...

In this episode, I’m joined by Ian Goodfellow, Staff Research Scientist at Google Brain and Sandy Huang, Phd Student in the EECS department at UC Berkeley, to discuss their work on the paper Adversarial Attacks on Neural Network Policies. If you’re a regular listener here you’ve probably heard of adversarial attacks, and have seen examples of deep learning based object detectors that can be fooled...

In this episode, we're joined by Raja Chatila, director of Intelligent Systems and Robotics at Pierre and Marie Curie University in Paris, and executive committee chair of the IEEE global initiative on ethics of intelligent and autonomous systems. Raja and I had a great chat about his research, which deals with robotic perception and discovery. We discuss the relationship between learning and disc...

Earlier this week, I had a chance to speak with Chris Shallue, Senior Software Engineer on the Google Brain Team, about his project and paper on “Exploring Exoplanets with Deep Learning.” This is a great story. Chris, inspired by a book he was reading, reached out on a whim to a Harvard astrophysics researcher, kicking off a collaboration and side project eventually leading to the discovery of two...

In this episode, I speak with Ksenia Konyushkova, Ph. D. student in the CVLab at Ecole Polytechnique Federale de Lausanne in Switzerland. Ksenia and I connected at NIPS in December to discuss her interesting research into ways we might apply machine learning to ease the challenge of creating labeled datasets for machine learning. The first paper we discuss is “Learning Active Learning from Data,”...

In this episode, I speak with Mike Del Balso, Product Manager for Machine Learning Platforms at Uber. Mike and I sat down last fall at the Georgian Partners Portfolio conference to discuss his presentation “Finding success with machine learning in your company.” In our discussion, Mike shares some great advice for organizations looking to get value out of machine learning. He also details some of...

For today’s show, the final episode of our Black in AI Series, I’m joined by Zenna Tavares, a PhD student in the both the department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Lab at MIT. I spent some time with Zenna after his talk at the Strange Loop conference titled “Running Programs in Reverse for Deeper AI.” Zenna shares some great insight into his wo...

In this episode, I speak with Sriraam Natarajan, Associate Professor in the Department of Computer Science at UT Dallas. While at NIPS a few months back, Sriraam and I sat down to discuss his work on Statistical Relational Artificial Intelligence. StarAI is the combination of probabilistic & statistical machine learning techniques with relational databases. We cover systems learning on top of rela...

In this episode, part 4 in our Black in AI series, i'm joined by Charles Onu, Phd Student at McGill University in Montreal & Founder of Ubenwa, a startup tackling the problem of infant mortality due to asphyxia. Using SVMs and other techniques from the field of automatic speech recognition, Charles and his team have built a model that detects asphyxia based on the audible noises the child makes up...

In today’s episode, I’m joined by Roland Memisevic, co-founder, CEO, and chief scientist at Twenty Billion Neurons. Roland joined me at the RE•WORK Deep Learning Summit in Montreal to discuss the work his company is doing to train deep neural networks to understand physical actions. In our conversation, we dig into video analysis and understanding, including how data-rich video can help us develop...

In this episode, the third in our Black in AI series, I speak with Ayanna Howard, Chair of the Interactive School of Computing at Georgia Tech. Ayanna joined me for a lively discussion about her work in the field of human-robot interaction. We dig deep into a couple of major areas she’s active in that have significant implications for the way we design and use artificial intelligence, namly pediat...

For today’s show, I'm joined by Nyalleng Moorosi, Senior Data Science Researcher at The Council for Scientific & Industrial Research or CSIR, in Pretoria, South Africa. In our discussion, we discuss two major projects that Nyalleng is apart of at the CSIR, one, a predictive policing use case, which focused on understanding and preventing rhino poaching in Kruger National Park, and the other, a hea...

In this episode I’m joined by Moustapha Cissé, Research Scientist at Facebook AI Research Lab (or FAIR) Paris. Moustapha’s broad research interests include the security and safety of AI systems, and we spend some time discussing his work on adversarial examples and systems that are robust to adversarial attacks. More broadly, we discuss the role of bias in datasets, and explore his vision for mode...

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 w...

In this episode i'm joined by Ilkka Korhonen, Vice President of Technology at Firstbeat, a company whose algorithms are embedded in fitness watches from companies like Garmin and Suunto and which use your heartbeat data to offer personalized insights into stress, fitness, recovery and sleep patterns. We cover a ton about Firstbeat in the conversation, including how they transform the sensor readin...

In this episode, I'm joined by Stuart Feffer, co-founder and CEO of Reality AI, which provides tools and services for engineers working with sensors and signals, and Brady Tsai, Business Development Manager at Koito, which develops automotive lighting solutions for car manufacturers. Stuart and Brady joined me at CES a few weeks ago after they announced a partnership to bring Adaptive Driving Beam...

In this episode, I'm joined by Andy Keller and Emile Chin-Dickey to discuss Intel's partnership with the Ferrari Challenge North American Series. Andy is a Deep Learning Data Scientist at Intel and Emile is Senior Manager of Marketing Partnerships at the company. In this show, Emile gives us a high-level overview of the Ferrari Challenge partnership and the goals of the collaboration. Andy & I the...

In this episode, I sit down with Alex Teichman, CEO and Co-Founder of Lighthouse, a company taking a new approach to the in-home smart camera. Alex and I dig into what exactly the Lighthouse product is, and all the interesting stuff inside, including its combination of 3D sensing, computer vision, and NLP. We also talk about Alex’s process for building the Lighthouse network architecture, they tec...

In this episode, I'm joined by Andrew Stein, computer vision engineer at consumer robotics company Anki, and his partner in crime Cozmo, a toy robot with tons of personality. Andrew joined me during the hustle and bustle of CES a few weeks ago to give me some insight into how Cozmo works, plays, and learns, and how he’s different from other consumer robots you may know, such as the Roomba. We disc...

In this episode i'm joined by Inmar Givoni, Autonomy Engineering Manager at Uber ATG, to discuss her work on the paper Min-Max Propagation, which was presented at NIPS last month in Long Beach. Inmar and I get into a meaty discussion about graphical models, including what they are and how they’re used, some of the challenges they present for both training and inference, and how and where they can...

In this episode, I speak with Arthur Gretton, Wittawat Jitkrittum, Zoltan Szabo and Kenji Fukumizu, who, alongside Wenkai Xu authored the 2017 NIPS Best Paper Award winner “A Linear-Time Kernel Goodness-of-Fit Test.” In our discussion, we cover what exactly a “goodness of fit” test is, and how it can be used to determine how well a statistical model applies to a given real-world scenario. The grou...