The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books
Apr 16, 2020 • 54min
Neural Architecture Search and Google’s New AutoML Zero with Quoc Le - #366
Quoc Le, a research scientist at Google known for his pioneering work on AutoML Zero and neural architecture search, dives into fascinating topics. He shares insights on using evolutionary methods for optimizing machine learning models and the challenges involved in scaling them. Quoc also discusses semi-supervised learning techniques that enhance data labeling and model performance, and even touches on the humorous side of language models, revealing how they generate unexpected puns and jokes. Tune in for a blend of cutting-edge AI and unexpected humor!
Apr 13, 2020 • 35min
Automating Electronic Circuit Design with Deep RL w/ Karim Beguir - #365
Karim Beguir, Co-founder and CEO of InstaDeep, discusses the groundbreaking DeepPCB platform that automates circuit board design using deep reinforcement learning. He outlines the challenges faced by traditional auto-routers and emphasizes the importance of computation in enhancing AI capabilities. The conversation dives into leveraging transfer learning for improved circuit design efficiency and celebrates a milestone with a spotlight paper at NeurIPS, highlighting the significance of compositional problem-solving in AI research.
Apr 9, 2020 • 49min
Neural Ordinary Differential Equations with David Duvenaud - #364
Join David Duvenaud, an Assistant Professor at the University of Toronto, as he shares his insights on Neural Ordinary Differential Equations (ODEs). He discusses how ODEs could revolutionize neural networks by offering continuous-depth modeling and tackling complex dynamics. David dives into their application in managing irregular medical time series data, emphasizing the efficiency of predictive analytics. He also touches on the balance between specialization and the exploration of diverse research interests, making this conversation a fascinating blend of theory and real-world application.
Apr 6, 2020 • 48min
The Measure and Mismeasure of Fairness with Sharad Goel - #363
Sharad Goel, an Assistant Professor at Stanford, specializes in applying machine learning to public policy. He dives into his work on discriminatory policing, discussing the impact of practices like Stop and Frisk. Goel critiques traditional definitions of algorithmic fairness and emphasizes the ethical implications in high-stakes environments like law enforcement. He advocates for data transparency and community engagement to reform inequitable systems, highlighting the need for balanced approaches in criminal risk assessments.
Apr 2, 2020 • 35min
Simulating the Future of Traffic with RL w/ Cathy Wu - #362
Cathy Wu, an MIT Assistant Professor, dives into her groundbreaking work using reinforcement learning to tackle mixed autonomy traffic challenges. She shares insights from her simulations of various traffic scenarios—like intersections and merges—revealing how autonomous vehicles can improve overall traffic efficiency. Wu emphasizes the surprising benefits even a few automated cars can have in reducing wait times and enhancing flow. Their interactions with human drivers and the implications for urban planning are also explored, sparking thought on the future of transportation.
Mar 30, 2020 • 49min
Consciousness and COVID-19 with Yoshua Bengio - #361
In this engaging discussion, Yoshua Bengio, a leading deep learning researcher and professor, shares his insights on the nature of consciousness and its link to artificial intelligence. He delves into his innovative work on a COVID-19 tracing app that prioritizes privacy, as well as machine learning's role in drug discovery. Bengio also touches on how consciousness influences adaptive learning and decision-making, highlighting the ongoing intersection between AI, brain sciences, and philosophy. A thought-provoking exploration of AI's potential for social good!
Mar 26, 2020 • 27min
Geometry-Aware Neural Rendering with Josh Tobin - #360
Josh Tobin, co-organizer of the Full Stack Deep Learning program and former research scientist at OpenAI, dives deep into geometry-aware neural rendering. He highlights the challenges in generating 3D scenes, the importance of domain randomization, and innovative methods bridging real-world data with simulations. The conversation also touches on the significance of encoder-decoder architectures in enhancing image rendering and how these techniques are revolutionizing AI applications in robotics.
Mar 23, 2020 • 1h 2min
The Third Wave of Robotic Learning with Ken Goldberg - #359
Ken Goldberg, a UC Berkeley professor specializing in robotic learning, shares fascinating insights about the challenges in robotic grasping, emphasizing the need for understanding physics and improving sensing technologies. He discusses the innovative applications of robots in telemedicine, agriculture, and even COVID-19 testing. The conversation also touches on the blend of robotics and art, showcasing projects like the Telegarden, and the importance of setting realistic expectations about robotic capabilities in healthcare and precision farming.
Mar 18, 2020 • 28min
Learning Visiolinguistic Representations with ViLBERT w/ Stefan Lee - #358
Stefan Lee, an assistant professor at Oregon State University, dives into the fascinating world of visiolinguistic representations with his groundbreaking work, ViLBERT. He explores how this model integrates visual and language tasks, shedding light on complex challenges like visual question answering. Lee discusses the PyRobot platform, which facilitates robotic navigation through natural language. The conversation also highlights the importance of grounded connections between modalities, as well as the implications of his research for visually impaired individuals.
Mar 16, 2020 • 34min
Upside-Down Reinforcement Learning with Jürgen Schmidhuber - #357
Jürgen Schmidhuber, Co-founder of NNAISENSE and a pioneer in AI known for developing the LSTM network, discusses groundbreaking advancements in AI. He delves into Upside-Down Reinforcement Learning, highlighting its application in controlling robotic hands and improving learning through experiential methods. The conversation covers the shift from passive to active learning in industrial AI technologies, such as soft robotics and drone inspections, showcasing how curiosity-driven approaches can revolutionize robotics and real-world applications.
