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

Today we close out our coverage of the ICLR series joined by Meg Mitchell, chief ethics scientist and researcher at Hugging Face. In our conversation with Meg, we discuss her participation in the WikiM3L Workshop, as well as her transition into her new role at Hugging Face, which has afforded her the ability to prioritize coding in her work around AI ethics. We explore her thoughts on the work hap...

Today we continue our ICLR coverage joined by Been Kim, a staff research scientist at Google Brain, and an ICLR 2022 Invited Speaker. Been, whose research has historically been focused on interpretability in machine learning, delivered the keynote Beyond interpretability: developing a language to shape our relationships with AI, which explores the need to study AI machines as scientific objects, i...

Today we’re joined by Auke Wiggers, an AI research scientist at Qualcomm. In our conversation with Auke, we discuss his team’s recent research on data compression using generative models. We discuss the relationship between historical compression research and the current trend of neural compression, and the benefit of neural codecs, which learn to compress data from examples. We also explore the p...

Today we’re joined by Irwan Bello, formerly a research scientist at Google Brain, and now on the founding team at a stealth AI startup. We begin our conversation with an exploration of Irwan’s recent paper, Designing Effective Sparse Expert Models, which acts as a design guide for building sparse large language model architectures. We discuss mixture of experts as a technique, the scalability of t...

Today we’re joined by friend of the show Timnit Gebru, the founder and executive director of DAIR, the Distributed Artificial Intelligence Research Institute. In our conversation with Timnit, we discuss her journey to create DAIR, their goals and some of the challenges shes faced along the way. We start is the obvious place, Timnit being “resignated” from Google after writing and publishing a pape...

Today we’re joined by Doina Precup, a research team lead at DeepMind Montreal, and a professor at McGill University. In our conversation with Doina, we discuss her recent research interests, including her work in hierarchical reinforcement learning, with the goal being agents learning abstract representations, especially over time. We also explore her work on reward specification for RL agents, wh...

Today we’re joined by Bharath Ramsundar, founder and CEO of Deep Forest Sciences. In our conversation with Bharath, we explore his work on the DeepChem, an open-source library for drug discovery, materials science, quantum chemistry, and biology tools. We discuss the challenges that biotech and pharmaceutical companies are facing as they attempt to incorporate AI into the drug discovery process, w...

Today we’re joined by Sebastian Raschka, an assistant professor at the University of Wisconsin-Madison and lead AI educator at Grid.ai. In our conversation with Sebastian, we explore his work around AI education, including the “hands-on” philosophy that he takes when building these courses, his recent book Machine Learning with PyTorch and Scikit-Learn, his advise to beginners in the field when th...

Today we’re joined by Thomas Wolf, co-founder and chief science officer at Hugging Face 🤗. We cover a ton of ground In our conversation, starting with Thomas’ interesting backstory as a quantum physicist and patent lawyer, and how that lead him to a career in machine learning. We explore how Hugging Face began, what the current direction is for the company, and how much of their focus is NLP and...

Today we’re joined by Murali Akula, a Sr. director of Software Engineering at Qualcomm. In our conversation with Murali, we explore his role at Qualcomm, where he leads the corporate research team focused on the development and deployment of AI onto Snapdragon chips, their unique definition of “full stack”, and how that philosophy permeates into every step of the software development process. We e...

Today we’re joined by Subutai Ahmad, VP of research at Numenta. While we’ve had numerous conversations about the biological inspirations of deep learning models with folks working at the intersection of deep learning and neuroscience, we dig into uncharted territory with Subutai. We set the stage by digging into some of fundamental ideas behind Numenta’s research and the present landscape of neuro...

Today we’re joined by Jennifer Glore, VP of customer engineering at SambaNova Systems. In our conversation with Jennifer, we discuss how, and why, Sambanova, who is primarily focused on building hardware to support machine learning applications, has built a GPT language model for the financial services industry. Jennifer shares her thoughts on the progress of industries like banking and finance, a...

Today we’re joined by Kamyar Azizzadenesheli, an assistant professor at Purdue University, to close out our AI Rewind 2021 series! In this conversation, we focused on all things deep reinforcement learning, starting with a general overview of the direction of the field, and though it might seem to be slowing, thats just a product of the light being shined constantly on the CV and NLP spaces. We di...

Today we’re joined by Rishabh Agarwal, a research scientist at Google Brain in Montreal. In our conversation with Rishabh, we discuss his recent paper Deep Reinforcement Learning at the Edge of the Statistical Precipice, which won an outstanding paper award at the most recent NeurIPS conference. In this paper, Rishabh and his coauthors call for a change in how deep RL performance is reported on be...

Today we’re joined by Rafael Gomez-Bombarelli, an assistant professor in the department of material science and engineering at MIT. In our conversation with Rafa, we explore his goal of ​​fusing machine learning and atomistic simulations for designing materials, a topic he spoke about at the recent SigOpt AI & HPC Summit. We discuss the two ways in which he thinks of material design, virtual scree...

Today we’re joined by Patrick Heimbach, a professor at the University of Texas working at the intersection of ML and oceanography. In our conversation with Patrick, we explore some of the challenges of computational oceanography, the potential use cases for machine learning in this field, as well as how it can be used to support scientists in solving simulation problems, and the role of differenti...

Today we continue our AI Rewind 2021 series joined by a friend of the show, assistant professor at Carnegie Mellon University, and AI Rewind veteran, Zack Lipton! In our conversation with Zack, we touch on recurring themes like “NLP Eating AI” and the recent slowdown in innovation in the field, the redistribution of resources across research problems, and where the opportunities for real breakthro...

Today we’re joined by Jonathan Le Roux, a senior principal research scientist at Mitsubishi Electric Research Laboratories (MERL). At MERL, Jonathan and his team are focused on using machine learning to solve the “cocktail party problem”, focusing on not only the separation of speech from noise, but also the separation of speech from speech. In our conversation with Jonathan, we focus on his paper...

Today we’re joined by Karianne Bergen, an assistant professor at Brown University. In our conversation with Karianne, we explore her work at the intersection of earthquake seismology and machine learning, where she’s working on interpretable data classification for seismology. We discuss some of the challenges that present themselves when trying to solve this problem, and the state of applying mac...

Today we’re joined by Arun Kumarm, an associate professor at UC San Diego. We had the pleasure of catching up with Arun prior to the Workshop on Databases and AI at NeurIPS 2021, where he delivered the talk “The New DBfication of ML/AI.” In our conversation, we explore this “database-ification” of machine learning, a concept analogous to the transformation of relational SQL computation. We discuss...

Today we’re joined by Meredith Broussard, an associate professor at NYU & research director at the NYU Alliance for Public Interest Technology. Meredith was a keynote speaker at the recent NeurIPS conference, and we had the pleasure of speaking with her to discuss her talk from the event, and her upcoming book, tentatively titled More Than A Glitch: What Everyone Needs To Know About Making Technol...

Today we’re joined by Sebastian Bubeck a sr principal research manager at Microsoft, and author of the paper A Universal Law of Robustness via Isoperimetry, a NeurIPS 2021 Outstanding Paper Award recipient. We begin our conversation with Sebastian with a bit of a primer on convex optimization, a topic that hasn’t come up much in previous interviews. We explore the problem that convex optimization...

Today we’re joined by friend of the show John Bohannon, the director of science at Primer AI, to help us showcase all of the great achievements and accomplishments in NLP in 2021! In our conversation, John shares his two major takeaways from last year, 1) NLP as we know it has changed, and we’re back into the incremental phase of the science, and 2) NLP is “eating” the rest of machine learning. We...

Happy New Year! We’re excited to kick off 2022 joined by Georgia Gkioxari, a research scientist at Meta AI, to showcase the best advances in the field of computer vision over the past 12 months, and what the future holds for this domain.  Welcome back to AI Rewind! In our conversation Georgia highlights the emergence of the transformer model in CV research, what kind of performance results we’re s...

Today we close out the 2021 NeurIPS series joined by Alison Gopnik, a professor at UC Berkeley and an invited speaker at the Causal Inference & Machine Learning: Why now? Workshop. In our conversation with Alison, we explore the question, “how is it that we can know so much about the world around us from so little information?,” and how her background in psychology, philosophy, and epistemology ha...