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.
551
Geometric Statistics in Machine Learning w/ geo...
In this episode we’re joined by Nina Miolane, researcher and lecturer at Stanford University. Nina and I recently spoke about her work in the field of geometric statistics in machine learning. Specifically, we discuss the application of Riemannian...
42 min
552
Milestones in Neural Natural Language Processin...
In this episode, we’re joined by Sebastian Ruder, a PhD student studying natural language processing at the National University of Ireland and a Research Scientist at text analysis startup Aylien. In our conversation, Sebastian and I discuss recent...
60 min
553
Natural Language Processing at StockTwits with ...
In this episode, we’re joined by Garrett Hoffman, Director of Data Science at Stocktwits. Garrett and I caught up at last month’s Strata Data conference, where he presented a tutorial on “Deep Learning Methods for NLP with Emphasis on Financial...
49 min
554
Advanced Reinforcement Learning & Data Science ...
In this, the final show of our Deep Learning Indaba Series, we speak with Vukosi Marivate, Chair of Data Science at the University of Pretoria and a co-organizer of the Indaba. My conversation with Vukosi fell into two distinct parts. The first part...
45 min
555
AI Ethics, Strategic Decisioning and Game Theor...
In this episode of our Deep Learning Indaba Series, we’re joined by Osonde Osoba, Engineer at RAND Corporation and Professor at the Pardee RAND Graduate School. Osonde and I spoke on the heels of the Indaba, where he presented on AI Ethics and...
46 min
556
Acoustic Word Embeddings for Low Resource Speec...
In this episode of our Deep Learning Indaba Series, we’re joined by Herman Kamper, Lecturer in the electrical and electronics engineering department at Stellenbosch University in SA and a co-organizer of the Indaba. Herman and I discuss his work on...
60 min
557
Learning Representations for Visual Search with...
In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe. Naila presented at the Indaba on computer vision, and in this discussion we...
40 min
558
Evaluating Model Explainability Methods with Sa...
In this, the first episode of the Deep Learning Indaba series, we’re joined by Sara Hooker, AI Resident at Google Brain. I had the pleasure of speaking with Sara in the run-up to the Indaba about her work on interpretability in deep neural networks....
62 min
559
Graph Analytic Systems with Zachary Hanif - TWi...
In this, the final episode of our Strata Data Conference series, we’re joined by Zachary Hanif, Director of Machine Learning at Capital One’s Center for Machine Learning. Zach led a session at Strata called “Network effects: Working with modern...
53 min
560
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
561
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
562
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
563
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
564
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
565
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
566
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
567
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
568
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
569
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
570
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
571
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
572
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
573
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
574
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
575
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