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

Latest Episodes:

Machine Learning for Equitable Healthcare Outcomes with Irene Chen - #479 Apr 29, 2021

Show notes

Today we’re joined by Irene Chen, a Ph.D. student at MIT.

Irene’s research is focused on developing new machine learning methods specifically for healthcare, through the lens of questions of equity and inclusion. In our conversation, we explore some of the various projects that Irene has worked on, including an early detection program for intimate partner violence.

We also discuss how she thinks about the long term implications of predictions in the healthcare domain, how she’s learned to communicate across the interface between the ML researcher and clinician, probabilistic approaches to machine learning for healthcare, and finally, key takeaways for those of you interested in this area of research.

The complete show notes for this episode can be found at https://twimlai.com/go/479.

AI Storytelling Systems with Mark Riedl - #478 Apr 26, 2021

Show notes

Today we’re joined by Mark Riedl, a Professor in the School of Interactive Computing at Georgia Tech. In our conversation with Mark, we explore his work building AI storytelling systems, mainly those that try and predict what listeners think will happen next in a story and how he brings together many different threads of ML/AI together to solve these problems. We discuss how the theory of mind is layered into his research, the use of large language models like GPT-3, and his push towards being able to generate suspenseful stories with these systems.

We also discuss the concept of intentional creativity and the lack of good theory on the subject, the adjacent areas in ML that he’s most excited about for their potential contribution to his research, his recent focus on model explainability, how he approaches problems of common sense, and much more!

The complete show notes for this episode can be found at https://twimlai.com/go/478.

Creating Robust Language Representations with Jamie Macbeth - #477 Apr 21, 2021

Show notes

Today we’re joined by Jamie Macbeth, an assistant professor in the department of computer science at Smith College.

In our conversation with Jamie, we explore his work at the intersection of cognitive systems and natural language understanding, and how to use AI as a vehicle for better understanding human intelligence. We discuss the tie that binds these domains together, if the tasks are the same as traditional NLU tasks, and what are the specific things he’s trying to gain deeper insights into.

One of the unique aspects of Jamie’s research is that he takes an “old-school AI” approach, and to that end, we discuss the models he handcrafts to generate language. Finally, we examine how he evaluates the performance of his representations if he’s not playing the SOTA “game,” what he bookmarks against, identifying deficiencies in deep learning systems, and the exciting directions for his upcoming research.

The complete show notes for this episode can be found at https://twimlai.com/go/477.

Reinforcement Learning for Industrial AI with Pieter Abbeel - #476 Apr 19, 2021

Show notes

Today we’re joined by Pieter Abbeel, a Professor at UC Berkeley, co-Director of the Berkeley AI Research Lab (BAIR), as well as Co-founder and Chief Scientist at Covariant.

In our conversation with Pieter, we cover a ton of ground, starting with the specific goals and tasks of his work at Covariant, the shift in needs for industrial AI application and robots, if his experience solving real-world problems has changed his opinion on end to end deep learning, and the scope for the three problem domains of the models he’s building.

We also explore his recent work at the intersection of unsupervised and reinforcement learning, goal-directed RL, his recent paper “Pretrained Transformers as Universal Computation Engines” and where that research thread is headed, and of course, his new podcast Robot Brains, which you can find on all streaming platforms today!

The complete show notes for this episode can be found at twimlai.com/go/476.

AutoML for Natural Language Processing with Abhishek Thakur - #475 Apr 15, 2021

Show notes

Today we’re joined by Abhishek Thakur, a machine learning engineer at Hugging Face, and the world’s first Quadruple Kaggle Grandmaster!

In our conversation with Abhishek, we explore his Kaggle journey, including how his approach to competitions has evolved over time, what resources he used to prepare for his transition to a full-time practitioner, and the most important lessons he’s learned along the way.

We also spend a great deal of time discussing his new role at HuggingFace, where he's building AutoNLP. We talk through the goals of the project, the primary problem domain, and how the results of AutoNLP compare with those from hand-crafted models. Finally, we discuss Abhishek’s book, Approaching (Almost) Any Machine Learning Problem.

The complete show notes for this episode can be found at https://twimlai.com/go/475.

Inclusive Design for Seeing AI with Saqib Shaikh - #474 Apr 12, 2021

Show notes

Today we’re joined by Saqib Shaikh, a Software Engineer at Microsoft, and the lead for the Seeing AI Project.

In our conversation with Saqib, we explore the Seeing AI app, an app “that narrates the world around you.” We discuss the various technologies and use cases for the app, and how it has evolved since the inception of the project, how the technology landscape supports projects like this one, and the technical challenges he faces when building out the app.

We also the relationship and trust between humans and robots, and how that translates to this app, what Saqib sees on the research horizon that will support his vision for the future of Seeing AI, and how the integration of tech like Apple’s upcoming “smart” glasses could change the way their app is used.

The complete show notes for this episode can be found at twimlai.com/go/474.

Theory of Computation with Jelani Nelson - #473 Apr 08, 2021

Show notes

Today we’re joined by Jelani Nelson, a professor in the Theory Group at UC Berkeley.

In our conversation with Jelani, we explore his research in computational theory, where he focuses on building streaming and sketching algorithms, random projections, and dimensionality reduction. We discuss how Jelani thinks about the balance between the innovation of new algorithms and the performance of existing ones, and some use cases where we’d see his work in action.

Finally, we talk through how his work ties into machine learning, what tools from the theorist’s toolbox he’d suggest all ML practitioners know, and his nonprofit AddisCoder, a 4 week summer program that introduces high-school students to programming and algorithms.

The complete show notes for this episode can be found at twimlai.com/go/473.

Human-Centered ML for High-Risk Behaviors with Stevie Chancellor - #472 Apr 05, 2021

Show notes

Today we’re joined by Stevie Chancellor, an Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota.

In our conversation with Stevie, we explore her work at the intersection of human-centered computing, machine learning, and high-risk mental illness behaviors. We discuss how her background in HCC helps shapes her perspective, how machine learning helps with understanding severity levels of mental illness, and some recent work where convolutional graph neural networks are applied to identify and discover new kinds of behaviors for people who struggle with opioid use disorder.

We also explore the role of computational linguistics and NLP in her research, issues in using social media data being used as a data source, and finally, how people who are interested in an introduction to human-centered computing can get started.

The complete show notes for this episode can be found at twimlai.com/go/472.

Operationalizing AI at Dataiku with Conor Jensen - #471 Apr 01, 2021

Show notes

In this episode, we’re joined by Dataiku’s Director of Data Science, Conor Jensen. In our conversation, we explore the panel he lead at TWIMLcon “AI Operationalization: Where the AI Rubber Hits the Road for the Enterprise,” discussing the ML journey of each panelist’s company, and where Dataiku fits in the equation.

The complete show notes for this episode can be found at https://twimlai.com/go/471.

ML Lifecycle Management at Algorithmia with Diego Oppenheimer - #470 Apr 01, 2021

Show notes

In this episode, we’re joined by Diego Oppenheimer, Founder and CEO of Algorithmia. In our conversation, we discuss Algorithmia’s involvement with TWIMLcon, as well as an exploration of the results of their recently conducted survey on the state of the AI market.

The complete show notes for this episode can be found at twimlai.com/go/470.

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