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 29, 2020 • 58min
Panel: Responsible Data Science in the Fight Against COVID-19 - #370
Join Rex Douglass, a computational social scientist, Rob Munro, a crowdsourced data expert, Lea Shanley, a champion of open science, and Gigi Yuen-Reed from IBM as they tackle how data science can ethically combat COVID-19. They dive into the perils of misinformation, the evolution of peer review amidst the pandemic, and the critical need for clear communication in public health. Discover their insights on the collaboration between scientists and citizens to enhance data quality and tackle the ongoing challenges in health crises.
Apr 27, 2020 • 41min
Adversarial Examples Are Not Bugs, They Are Features with Aleksander Madry - #369
Aleksander Madry, a faculty member at MIT specializing in machine learning robustness, dives into the intriguing world of adversarial examples. He argues these examples shouldn't be seen as mere bugs but as inherent features of AI systems. The conversation highlights the mismatch between human expectations and machine perception, stressing the need for new methodologies to improve interpretability. Madry also shares insights on using robust classifiers for image synthesis and navigates the dual nature of AI technologies, urging a deeper understanding of their implications.
6 snips
Apr 23, 2020 • 42min
AI for Social Good: Why "Good" isn't Enough with Ben Green - #368
Ben Green, a PhD candidate at Harvard and research fellow at NYU's AI Now Institute, dives into the ethics of AI and its societal implications. He argues that the concept of 'good' in technology isn't enough without a clear definition and a theory of change. The discussion reveals how algorithmic biases can impact marginalized communities and highlights the need for ethical considerations in AI education. Ben also shares insights on the challenges of implementing AI in urban settings and the importance of understanding the political context surrounding technological advancements.
Apr 20, 2020 • 38min
The Evolution of Evolutionary AI with Risto Miikkulainen - #367
Risto Miikkulainen, Associate VP of Evolutionary AI at Cognizant and a professor at the University of Texas at Austin, discusses the transformative power of evolutionary AI. He highlights its creative problem-solving capabilities in diverse industries like healthcare and manufacturing. Risto dives into neural architecture search, which automates network design, and explores the evolutionary advancements in AI that foster innovative solutions. He also addresses the need for AI standardization and advocates for responsible usage that promotes societal benefits.
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!
