The TWIML AI Podcast (formerly This W...
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
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Diversification in Recommender Systems with Ahs...
In this episode of our Strata Data conference series, we’re joined by Ahsan Ashraf, data scientist at Pinterest. In our conversation, Ahsan and I discuss his presentation from the conference, “Diversification in recommender systems: Using topical...
43 min
502
The Fastai v1 Deep Learning Framework with Jere...
In today's episode we’ll be taking a break from our and presenting a special conversation with Jeremy Howard, founder and researcher at Fast.ai. Fast.ai is a company many of our listeners are quite familiar with due to their popular deep learning...
70 min
503
Federated ML for Edge Applications with Justin ...
In this episode of our Strata Data conference series, we’re joined by Justin Norman, Director of Research and Data Science Services at Cloudera Fast Forward Labs. Fast Forward Labs was an Applied AI research firm and consultancy founded by Hilary...
46 min
504
Exploring Dark Energy & Star Formation w/ ML wi...
In today’s episode of our Strata Data series, we’re joined by Viviana Acquaviva, Associate Professor at City Tech, the New York City College of Technology. Viviana led a tutorial at the conference, titled “Learning Machine Learning using...
39 min
505
Document Vectors in the Wild with James Dreiss ...
In this episode of our Strata Data series we’re joined by James Dreiss, Senior Data Scientist at international news syndicate Reuters. James and I sat down to discuss his talk from the conference “Document vectors in the wild, building a content...
39 min
506
Applied Machine Learning for Publishers with Na...
In today’s episode we’re joined by Naveed Ahmad, Senior Director of data engineering and machine learning at Hearst Newspapers. A few months ago, Naveed gave a talk at the Google Cloud Next Conference on “How Publishers Can Take Advantage of...
38 min
507
Anticipating Superintelligence with Nick Bostro...
In this episode, we’re joined by Nick Bostrom, professor in the faculty of philosophy at the University of Oxford, where he also heads the Future of Humanity Institute, a multidisciplinary institute focused on answering big-picture questions for...
43 min
508
Can We Train an AI to Understand Body Language?...
In this episode, we’re joined by Hanbyul Joo, a PhD student in the Robotics Institute at Carnegie Mellon University. Han, who is on track to complete his thesis at the end of the year, is working on what is called the “Panoptic Studio,” a...
50 min
509
Biological Particle Identification and Tracking...
In today’s episode we’re joined by Jay Newby, Assistant Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. Jay joins us to discuss his work applying deep learning to biology, including his paper...
44 min
510
AI for Content Creation with Debajyoti Ray - TW...
In today’s episode we’re joined by Debajyoti Ray, Founder and CEO of RivetAI, a startup producing AI-powered tools for storytellers and filmmakers. Rivet’s tools are inspired in part by the founders’ collaboration with the team that created...
54 min
511
Deep Reinforcement Learning Primer and Research...
Today we’re joined by Kamyar Azizzadenesheli, PhD student at the University of California, Irvine, and visiting researcher at Caltech where he works with Anima Anandkumar, who you might remember from . We begin with a reinforcement learning primer...
93 min
512
OpenAI Five with Christy Dennison - TWiML Talk ...
Today we’re joined by Christy Dennison, Machine Learning Engineer at OpenAI. Since joining OpenAI earlier this year, Christy has been working on OpenAI’s efforts to build an AI-powered agent to play the DOTA 2 video game. Our conversation begins...
47 min
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How ML Keeps Shelves Stocked at Home Depot with...
Today we’re joined by Pat Woowong, principal engineer in the applied machine intelligence group at The Home Depot. We discuss a project that Pat recently presented at the Google Cloud Next conference which used machine learning to predict shelf-out...
44 min
514
Contextual Modeling for Language and Vision wit...
Today we’re joined by Nasrin Mostafazadeh, Senior AI Research Scientist at New York-based Elemental Cognition. Our conversation focuses on Nasrin’s work in event-centric contextual modeling in language and vision, which she sees as a means of...
48 min
515
ML for Understanding Satellite Imagery at Scale...
Today we’re joined by Kyle Story, computer vision engineer at Descartes Labs. Kyle and I caught up after his recent talk at the Google Cloud Next Conference titled “How Computers See the Earth: A Machine Learning Approach to Understanding...
55 min
516
Generating Ground-Level Images From Overhead Im...
Today we’re joined by Yi Zhu, a PhD candidate at UC Merced focused on geospatial image analysis. In our conversation, Yi and I take a look at his recent paper “.” Yi and I discuss the goal of this research, which is to train effective land-use...
37 min
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Vision Systems for Planetary Landers and Drones...
Today we’re joined by Larry Matthies, Sr. Research Scientist and head of computer vision in the mobility and robotics division at JPL. Larry joins us on the heels of two presentations at this year’s CVPR conference, the first on Onboard Stereo...
42 min
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Learning Semantically Meaningful and Actionable...
In this episode I'm joined by Ashutosh Saxena, a veteran of Andrew Ng’s Stanford Machine Learning Group, and co-founder and CEO of Caspar.ai. Ashutosh and I discuss his RoboBrain project, a computational system that creates semantically meaningful...
44 min
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AI Innovation for Clinical Decision Support wit...
In this episode I speak with Joe Connor, Founder of Experto Crede. Joe’s been listening to the podcast for a while and he and I connected after he reached out to discuss an article I wrote regarding AI in the healthcare space. In this conversation,...
41 min
520
Dynamic Visual Localization and Segmentation wi...
In this episode I'm joined by Laura Leal-Taixé, Professor at the Technical University of Munich where she leads the Dynamic Vision and Learning Group, and 2017 recipient of prestigious Sofja Kovalevskaja Award. In our conversation, we discuss several...
43 min
521
Conversational AI for the Intelligent Workplace...
In this episode I'm joined by Gillian McCann, Head of Cloud Engineering and AI at Workgrid Software. Workgrid offers an intelligent workplace assistant that integrates with a variety of business tools and systems. In our conversation, which...
35 min
522
Computer Vision and Intelligent Agents for Wild...
In this episode, I'm joined by Jason Holmberg, Executive Director and Director of Engineering at WildMe. Wildme’s Wildbook and Whaleshark.org are both open source computer vision based conservation projects, that have been compared to a facebook for...
47 min
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Pragmatic Deep Learning for Medical Imagery wit...
In this episode I'm joined by Prashant Warier, CEO and Co-Founder of Qure.ai, a company building AI-powered software for radiology. In our conversation, Prashant and I discuss the company’s work building products for interpreting head CT scans and...
35 min
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Taskonomy: Disentangling Transfer Learning for ...
In this episode I'm joined by Amir Zamir, Postdoctoral researcher at both Stanford & UC Berkeley. Amir joins us fresh off of winning the 2018 CVPR Best Paper Award for co-authoring In this work, Amir and his coauthors explore the relationships...
46 min
525
Predicting Metabolic Pathway Dynamics w/ Machin...
In today’s episode I’m joined by Zak Costello, post-doctoral fellow at the Joint BioEnergy Institute. Zak joins me to discuss his recent paper, “A machine learning approach to predict metabolic pathway dynamics from time-series multiomics...
38 min