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

Today we’re joined by Li Jiang, a distinguished engineer at Microsoft working on Azure Speech.  In our conversation with Li, we discuss his journey across 27 years at Microsoft, where he’s worked on, among other things, audio and speech recognition technologies. We explore his thoughts on the advancements in speech recognition over the past few years, the challenges, and advantages, of using eithe...

Today we’re joined by Sandra Wacther, an associate professor and senior research fellow at the University of Oxford.  Sandra’s work lies at the intersection of law and AI, focused on what she likes to call “algorithmic accountability”. In our conversation, we explore algorithmic accountability in three segments, explainability/transparency, data protection, and bias, fairness and discrimination. W...

Today we’re joined by Dillon Erb, CEO of Paperspace.  If you’re not familiar with Dillon, he joined us about a year ago to discuss Machine Learning as a Software Engineering Discipline; we strongly encourage you to check out that interview as well. In our conversation, we explore the idea of compositional AI, and if it is the next frontier in a string of recent game-changing machine learning devel...

Today we’re joined by Yanshuai Cao, a senior research team lead at Borealis AI. In our conversation with Yanshuai, we explore his work on Turing, their natural language to SQL engine that allows users to get insights from relational databases without having to write code. We do a bit of compare and contrast with the recently released Codex Model from OpenAI, the role that reasoning plays in solvin...

Today we’re joined by Yejin Choi, a professor at the University of Washington. We had the pleasure of catching up with Yejin after her keynote interview at the recent Stanford HAI “Foundational Models” workshop. In our conversation, we explore her work at the intersection of natural language generation and common sense reasoning, including how she defines common sense, and what the current state o...

Today we’re joined by Konrad Tollmar, research director at Electronic Arts and an associate professor at KTH.  In our conversation, we explore his role as the lead of EA’s applied research team SEED and the ways that they’re applying ML/AI across popular franchises like Apex Legends, Madden, and FIFA. We break down a few papers focused on the application of ML to game testing, discussing why deep...

Today we’re joined by Kai-Fu Lee, chairman and CEO of Sinovation Ventures and author of AI 2041: Ten Visions for Our Future.  In AI 2041, Kai-Fu and co-author Chen Qiufan tell the story of how AI could shape our future through a series of 10 “scientific fiction” short stories. In our conversation with Kai-Fu, we explore why he chose 20 years as the time horizon for these stories, and dig into a fe...

Today we’re joined by Daniela Rus, director of CSAIL & Deputy Dean of Research at MIT.  In our conversation with Daniela, we explore the history of CSAIL, her role as director of one of the most prestigious computer science labs in the world, how she defines robots, and her take on the current AI for robotics landscape. We also discuss some of her recent research interests including soft robotics,...

Today we’re joined by Alexander Richard, a research scientist at Facebook Reality Labs, and recipient of the ICLR Best Paper Award for his paper “Neural Synthesis of Binaural Speech From Mono Audio.”  We begin our conversation with a look into the charter of Facebook Reality Labs, and Alex’s specific Codec Avatar project, where they’re developing AR/VR for social telepresence (applications like th...

Today we’re joined by Alona Fyshe, an assistant professor at the University of Alberta.  We caught up with Alona on the heels of an interesting panel discussion that she participated in, centered around improving AI systems using research about brain activity. In our conversation, we explore the multiple types of brain images that are used in this research, what representations look like in these...

Today we’re joined by Samory Kpotufe, an associate professor at Columbia University and program chair of the 2021 Conference on Learning Theory (COLT).  In our conversation with Samory, we explore his research at the intersection of machine learning, statistics, and learning theory, and his goal of reaching self-tuning, adaptive algorithms. We discuss Samory’s research in transfer learning and oth...

Today we’re joined by Eric Rice, associate professor at USC, and the co-director of the USC Center for Artificial Intelligence in Society.  Eric is a sociologist by trade, and in our conversation, we explore how he has made extensive inroads within the machine learning community through collaborations with ML academics and researchers. We discuss some of the most important lessons Eric has learned...

Today we’re joined by José Miguel Hernández-Lobato, a university lecturer in machine learning at the University of Cambridge. In our conversation with Miguel, we explore his work at the intersection of Bayesian learning and deep learning. We discuss how he’s been applying this to the field of molecular design and discovery via two different methods, with one paper searching for possible chemical r...

Today we’re joined by return guest Greg Brockman, co-founder and CTO of OpenAI. We had the pleasure of reconnecting with Greg on the heels of the announcement of Codex, OpenAI’s most recent release. Codex is a direct descendant of GPT-3 that allows users to do autocomplete tasks based on all of the publicly available text and code on the internet. In our conversation with Greg, we explore the dist...

Today we’re joined by Rose Yu, an assistant professor at the Jacobs School of Engineering at UC San Diego.  Rose’s research focuses on advancing machine learning algorithms and methods for analyzing large-scale time-series and spatial-temporal data, then applying those developments to climate, transportation, and other physical sciences. We discuss how Rose incorporates physical knowledge and part...

Today we’re joined by Bryan Catanzaro, vice president of applied deep learning research at NVIDIA. Most folks know Bryan as one of the founders/creators of cuDNN, the accelerated library for deep neural networks. In our conversation, we explore his interest in high-performance computing and its recent overlap with AI, his current work on Megatron, a framework for training giant language models, an...

Today we close out our 2021 ICML series joined by Lina Montoya, a postdoctoral researcher at UNC Chapel Hill.  In our conversation with Lina, who was an invited speaker at the Neglected Assumptions in Causal Inference Workshop, we explored her work applying Optimal Dynamic Treatment (ODT) to understand which kinds of individuals respond best to specific interventions in the US criminal justice sys...

Today we continue our ICML series joined by Gustavo Malkomes, a research engineer at Intel via their recent acquisition of SigOpt.  In our conversation with Gustavo, we explore his paper Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design, which focuses on a novel algorithmic solution for the iterative model search process. This new algorithm empow...

Today we kick off our ICML coverage joined by Virginia Smith, an assistant professor in the Machine Learning Department at Carnegie Mellon University.  In our conversation with Virginia, we explore her work on cross-device federated learning applications, including where the distributed learning aspects of FL are relative to the privacy techniques. We dig into her paper from ICML, Ditto: Fair and...

Today we’re joined by Errol Koolmeister, the head of AI foundation at H&M Group. In our conversation with Errol, we explore H&M’s AI journey, including its wide adoption across the company in 2016, and the various use cases in which it's deployed like fashion forecasting and pricing algorithms. We discuss Errol’s first steps in taking on the challenge of scaling AI broadly at the company, the valu...

Today we’re joined by Stefano Soatto, VP of AI applications science at AWS and a professor of computer science at UCLA.  Our conversation with Stefano centers on recent research of his called Graceful AI, which focuses on how to make trained systems evolve gracefully. We discuss the broader motivation for this research and the potential dangers or negative effects of constantly retraining ML model...

Today we’re joined by Suchi Saria, the founder and CEO of Bayesian Health, the John C. Malone associate professor of computer science, statistics, and health policy, and the director of the machine learning and healthcare lab at Johns Hopkins University.  Suchi shares a bit about her journey to working in the intersection of machine learning and healthcare, and how her research has spanned across...

Today we’re joined by a friend of the show Jeff Gehlhaar, VP of technology and the head of AI software platforms at Qualcomm.  In our conversation with Jeff, we cover a ton of ground, starting with a bit of exploration around ML compilers, what they are, and their role in solving issues of parallelism. We also dig into the latest additions to the Snapdragon platform, AI Engine Direct, and how it w...

Today we continue our AI in Innovation series joined by Dan Bohus, senior principal researcher at Microsoft Research, and Siddhartha Sen, a principal researcher at Microsoft Research.  In this conversation, we use a pair of research projects, Maia Chess and Situated Interaction, to springboard us into a conversation about the evolution of human-AI interaction. We discuss both of these projects ind...

Today we’re joined by Julieta Martinez, a senior research scientist at recently announced startup Waabi.  Julieta was a keynote speaker at the recent LatinX in AI workshop at CVPR, and our conversation focuses on her talk “What do Large-Scale Visual Search and Neural Network Compression have in Common,” which shows that multiple ideas from large-scale visual search can be used to achieve state-of-...