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

Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the context of models, the various types of models covered in the book, and the importanc...

Today we’re joined by Abeba Birhane, PhD Student at University College Dublin and author of the recent paper Algorithmic Injustices: Towards a Relational Ethics, which was the recipient of the Best Paper award at the 2019 Black in AI Workshop at NeurIPS. In our conversation, break down the paper and the thought process around AI ethics, the “harm of categorization,” how ML generally doesn’t accoun...

Today we’re excited to kick off our annual Black in AI Series joined by Nemo Semret, CTO of Gro Intelligence. Gro provides an agricultural data platform dedicated to improving global food security, focused on applying AI at macro scale. In our conversation with Nemo, we discuss Gro’s approach to data acquisition, how they apply machine learning to various problems, and their approach to modeling.

Today we’re joined by Ryan Rogers, Senior Software Engineer at LinkedIn, to discuss his paper “Practical Differentially Private Top-k Selection with Pay-what-you-get Composition.” In our conversation, we discuss how LinkedIn allows its data scientists to access aggregate user data for exploratory analytics while maintaining its users’ privacy through differential privacy, and the connection betwee...

Today we conclude the KubeCon ‘19 series joined by Erez Cohen, VP of CloudX & AI at Mellanox, who we caught up with before his talk “Networking Optimizations for Multi-Node Deep Learning on Kubernetes.” In our conversation, we discuss NVIDIA’s recent acquisition of Mellanox, the evolution of technologies like RDMA and GPU Direct, how Mellanox is enabling Kubernetes and other platforms to take adva...

Today we’re joined by Bob Killen, Research Cloud Administrator at the University of Michigan. In our conversation, we explore how Bob and his group at UM are deploying Kubernetes, the user experience, and how those users are taking advantage of distributed computing. We also discuss if ML/AI focused Kubernetes users should fear that the larger non-ML/AI user base will negatively impact their featu...

Today we kick off our KubeCon ‘19 series joined by Haytham AbuelFutuh and Ketan Umare, a pair of software engineers at Lyft. We caught up with Haytham and Ketan at KubeCo, where they were presenting their newly open-sourced, cloud-native ML and data processing platform, Flyte. We discuss what prompted Ketan to undertake this project and his experience building Flyte, the core value proposition, wh...

Today Robert Osazuwa Ness, ML Research Engineer at Gamalon and Instructor at Northeastern University joins us to discuss Causality, what it means, and how that meaning changes across domains and users, and our upcoming study group based around his new course sequence, “Causal Modeling in Machine Learning," for which you can find details at twimlai.com/community.

Today we’re joined by Jannis Born, Ph. D. student at ETH & IBM Research Zurich, to discuss his “PaccMann^RL” research. Jannis details how his background in computational neuroscience applies to this research, how RL fits into the goal of anticancer drug discovery, the effect DL has had on his research, and of course, a step-by-step walkthrough of how the framework works to predict the sensitivity...

Today we’re joined by Blaise Aguera y Arcas, a distinguished scientist at Google. We had the pleasure of catching up with Blaise at NeurIPS last month, where he was invited to speak on “Social Intelligence.” In our conversation, we discuss his role at Google, and his team’s approach to machine learning, and of course his presentation, in which he touches discussing today’s ML landscape, the gap be...

Today we’re joined by Pablo Samuel Castro, Staff Research Software Developer at Google. We cover a lot of ground in our conversation, including his love for music, and how that has guided his work on the Lyric AI project, and a few of his papers including “A Geometric Perspective on Optimal Representations for Reinforcement Learning” and “Estimating Policy Functions in Payments Systems using Deep...

Today we close out AI Rewind 2019 joined by Amir Zamir, who recently began his tenure as an Assistant Professor of Computer Science at the Swiss Federal Institute of Technology. Amir joined us back in 2018 to discuss his CVPR Best Paper winner, and in today’s conversation, we continue with the thread of Computer Vision. In our conversation, we discuss quite a few topics, including Vision-for-Robot...

Today we continue the AI Rewind 2019 joined by friend-of-the-show Nasrin Mostafazadeh, Senior AI Research Scientist at Elemental Cognition. We caught up with Nasrin to discuss the latest and greatest developments and trends in Natural Language Processing, including Interpretability, Ethics, and Bias in NLP, how large pre-trained models have transformed NLP research, and top tools and frameworks in...

Today we keep the 2019 AI Rewind series rolling with friend-of-the-show Timnit Gebru, a research scientist on the Ethical AI team at Google. A few weeks ago at NeurIPS, Timnit joined us to discuss the ethics and fairness landscape in 2019. In our conversation, we discuss diversification of NeurIPS, with groups like Black in AI, WiML and others taking huge steps forward, trends in the fairness comm...

Today we continue to review the year that was 2019 via our AI Rewind series, and do so with friend of the show Chelsea Finn, Assistant Professor in the CS Department at Stanford University. Chelsea’s research focuses on Reinforcement Learning, so we couldn’t think of a better person to join us to discuss the topic. In this conversation, we cover topics like Model-based RL, solving hard exploration...

Today we kick off our 2019 AI Rewind Series joined by Zack Lipton, Professor at CMU. You might remember Zack from our conversation earlier this year, “Fairwashing” and the Folly of ML Solutionism. In today's conversation, Zack recaps advancements across the vast fields of Machine Learning and Deep Learning, including trends, tools, research papers and more. We want to hear from you! Send your thou...

Today we close out our 2019 NeurIPS series with Mohamed Sidahmed, Machine Learning and Artificial Intelligence R&D Manager at Shell. In our conversation, we discuss two papers Mohamed and his team submitted to the conference this year, Accelerating Least Squares Imaging Using Deep Learning Techniques, and FaciesNet: Machine Learning Applications for Facies Classification in Well Logs. The show not...

Today we’re joined by Daphne Koller, co-Founder and former co-CEO of Coursera and Founder and CEO of Insitro. In our conversation, discuss the current landscape of pharmaceutical drugs and drug discovery, including the current pricing of drugs, and an overview of Insitro’s goal of using ML as a “compass” in drug discovery. We also explore how Insitro functions as a company, their focus on the biol...

Today we continue our 2019 NeurIPS coverage, this time around joined by Blake Richards, Assistant Professor at McGill University and a Core Faculty Member at Mila. Blake was an invited speaker at the Neuro-AI Workshop, and presented his research on “Sensory Prediction Error Signals in the Neocortex.” In our conversation, we discuss a series of recent studies on two-photon calcium imaging. We talk...

Today we’re joined by Celeste Kidd, Assistant Professor at UC Berkeley, to discuss her invited talk “How to Know” which details her lab’s research about the core cognitive systems people use to guide their learning about the world. We explore why people are curious about some things but not others, and how past experiences and existing knowledge shape future interests, why people believe what they...

Today we’re joined by Feng Yan, Assistant Professor at the University of Nevada, Reno to discuss ALERTWildfire, a camera-based network infrastructure that captures satellite imagery of wildfires. In our conversation, Feng details the development of the machine learning models and surrounding infrastructure. We also talk through problem formulation, challenges with using camera and satellite data i...

Today we’re joined by Dave Castillo, Managing VP for ML at Capital One and head of their Center for Machine Learning. In our conversation, we explore Capital One’s transition from “lab-based” ML to enterprise-wide adoption and support of ML, surprising ML use cases, their current platform ecosystem, their design vision in building this into a larger, all-encompassing platform, pain points in build...

Today we’re joined by Bryton Shang, Founder & CEO at Aquabyte, a company focused on the application of computer vision to various fish farming use cases. In our conversation, we discuss how Bryton identified the various problems associated with mass fish farming, challenges developing computer algorithms that can measure the height and weight of fish, assess issues like sea lice, and how they’re d...

Today we kick off our re:Invent 2019 series with Ville Tuulos, Machine Learning Infrastructure Manager at Netflix. At re:Invent, Netflix announced the open-sourcing of Metaflow, their “human-centric framework for data science.” In our conversation, we discuss all things Metaflow, including features, user experience, tooling, supported libraries, and much more. If you’re interested in checking out...

Today we’re joined by Stephen Merity, an independent researcher focused on NLP and Deep Learning. In our conversation, we discuss Stephens latest paper, Single Headed Attention RNN: Stop Thinking With Your Head, detailing his primary motivations behind the paper, the decision to use SHA-RNNs for this research, how he built and trained the model, his approach to benchmarking, and finally his goals...