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49:09

Principle-centric AI with Adrien Gaidon – #575

This week, we continue our conversations around the topic of Data-Centric AI joined by a friend of the show Adrien Gaidon, the head of ML research at the Toyota Research Institute (TRI). In our chat, Adrien expresses a fourth, somewhat contrarian, viewpoint to the three prominent schools of thought that organizations tend to fall into, […]

40:23

Data Debt in Machine Learning with D. Sculley – #574

Today we kick things off with a conversation with D. Sculley, a director on the Google Brain team. Many listeners of today’s show will know D. from his work on the paper, The Hidden Technical Debt in Machine Learning Systems, and of course, the infamous diagram. D. has recently translated the idea of technical debt […]

42:26

AI for Enterprise Decisioning at Scale with Rob Walker – #573

Today we’re joined by Rob Walker, vp of decisioning & analytics and gm of one-to-one customer engagement at Pegasystems. Rob, who you might know from his previous appearances on the podcast, joins us to discuss his work on AI and ML in the context of customer engagement and decisioning, the various problems that need to […]

46:04

Data Rights, Quantification and Governance for Ethical AI with Margaret Mitchell – #572

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 […]

50:32

Studying Machine Intelligence with Been Kim – #571

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 […]

39:21

Advances in Neural Compression with Auke Wiggers – #570

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 […]

52:45

Mixture-of-Experts and Trends in Large-Scale Language Modeling with Irwan Bello – #569

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 […]

01:08:02

Tech Special Docker for Data Science @ TWiML Online Meetup EMEA 4 March 2019 1080p

**SUBSCRIBE AND TURN ON NOTIFICATIONS** **twimlai.com** This video is a recap of our March 2019 EMEA TWiML Online Meetup. In this month’s community segment, we discuss the upcoming EMEA Meetup in April, the progress of the v3 Deep Learning Part 1 study group, the preparation for the v3 Deep Learning Part 2 course and study […]

56:07

Daring to DAIR: Distributed AI Research with Timnit Gebru – Talk 568

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, its goals, and some of the challenges she’s faced along the way. We start is the obvious place, Timnit being […]

48:18

Calvin Seward Interview – Deep Learning for Warehouse Operations

This week, I’m happy to bring you my interview with Calvin Seward, a research scientist with Berlin, Germany based Zalando. While our American listeners might not know the name Zalando, they’re one of the largest e-commerce companies in Europe with a focus on fashion and shoes. Calvin is a research scientist there, while also pursuing […]

39:14

Librosa: Audio and Music Processing in Python with Brian McFee – TWiML Talk #263

Today we continue our PyDataSci series joined by Brian McFee, assistant professor of music technology and data science at NYU, and creator of LibROSA, a python package for music and audio analysis. Brian walks us through his experience building LibROSA, including: • Detailing the core functions provided in the library, • His experience working within […]

52:16

Hierarchical and Continual RL with Doina Precup – #567

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 […]

34:46

Katie Driggs-Campbell Interview – Modeling Human Drivers for Autonomous Driving

We are back with our third show this week, episode 3 of our Autonomous Vehicles Series. My guest this time is Katie Driggs-Campbell, PostDoc in the Intelligent Systems Lab at Stanford University’s Department of Aeronautics and Astronautics. Katie joins us to discuss her research into human behavioral modeling and control systems for self-driving vehicles. Katie […]

47:03

Song Han Interview – Deep Gradient Compression for Distributed Training

On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed training for deep neural networks and the idea of compressing the gradient exchange to allow it to be done more efficiently. Song details the evolution […]

30:42

Open-Source Drug Discovery with DeepChem with Bharath Ramsundar – #566

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 […]

43:11

Advancing Hands-On Machine Learning Education with Sebastian Raschka – #565

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 […]

01:02:20

Playing Atari with Deep Reinforcement Learning – TWiML Online Meetup – March 2018

This video is a recap of our March 2018 TWiML Online Meetup. In our community segment we had a very fun and wide ranging discussion about freezing your brain, ML and AI in the healthcare space, and more. Community member Nicholas Teague,‏ who goes by @_NicT_ on twitter, also briefly spoke about his essay “A […]

46:01

Biological Particle Identification and Tracking with Jay Newby – TWiML Talk #179

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 “Deep neural networks automate detection for tracking of submicron scale particles in 2D and 3D.” In our […]

52:12

Big Science and Embodied Learning at Hugging Face 🤗 with Thomas Wolf – #564

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 […]

32:08

Full-Stack AI Systems Development with Murali Akula – #563

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 […]

54:51

100x Improvements in Deep Learning Performance with Sparsity with Subutai Ahmad – #562

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 […]

01:07:33

TWiML x Fast ai v3 Deep Learning Part 2 Study Group – Lesson 15 – Spring 2019 1080p

**SUBSCRIBE AND TURN ON NOTIFICATIONS** **twimlai.com** This video is a recap of our TWiML Online Study Group. In this session, we had a mini presentation on “Imagenet-Trained CNNs are Biased Towards Texture; Increasing Shape Bias Improves Accuracy and Robustness” and discussion. It’s not too late to join the study group. Just follow these simple steps: […]

49:54

Rob Munro Interview – Human-in-the-Loop AI for Emergency Response & More

In this episode, I chat with Rob Munro, CTO of the newly branded Figure Eight, formerly known as CrowdFlower. Figure Eight’s Human-in-the-Loop AI platform supports data science & machine learning teams working on autonomous vehicles, consumer product identification, natural language processing, search relevance, intelligent chatbots, and more. Rob and I had a really interesting discussion […]

44:19

Scaling BERT and GPT-3 for Financial Services with Jennifer Glore – #561

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 […]