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
Jul 29, 2019 • 37min
Environmental Impact of Large-Scale NLP Model Training with Emma Strubell - TWIML Talk #286
In this discussion, Emma Strubell, a visiting scientist at Facebook AI Research and future professor at Carnegie Mellon, dives into the environmental costs of NLP model training. She reveals findings from her pivotal paper on the carbon emissions linked to deep learning despite accuracy improvements. Emma also discusses how businesses are responding to environmental concerns and the importance of developing efficient, sustainable NLP practices. Her insights bridge cutting-edge research with real-world applications, offering a vision for greener AI.
Jul 25, 2019 • 1h 15min
“Fairwashing” and the Folly of ML Solutionism with Zachary Lipton - TWIML Talk #285
Zachary Lipton, Assistant Professor at CMU's Tepper School of Business, dives into the intersection of machine learning and healthcare. He highlights the importance of human expertise in AI decision-making and critiques the concept of 'fairwashing' in tech. The conversation touches on the challenges of applying machine learning in medical contexts, discussing the necessity for robust models that account for real-world complexities. Additionally, Lipton explores the ethical dimensions of algorithmic decision-making and the gap between theoretical fairness claims and practical realities.
Jul 22, 2019 • 41min
Retinal Image Generation for Disease Discovery with Stephen Odaibo - TWIML Talk #284
In this discussion, Dr. Stephen Odaibo, Founder and CEO of RETINA-AI Health Inc., shares his unique journey through medicine and AI, merging his expertise in math and ophthalmology. He delves into how his startup uses machine learning for retinal image analysis, tackling diabetic retinopathy and enhancing healthcare. Stephen emphasizes the importance of quality data over quantity in machine learning, explores the evolving landscape of AI and the necessity of domain expertise, and discusses innovation beyond major corporations in the data-driven world.
Jul 18, 2019 • 51min
Real world model explainability with Rayid Ghani - TWiML Talk #283
Rayid Ghani, the Director of the Center for Data Science and Public Policy at the University of Chicago, shares insights on applying machine learning for social good. He explores the crucial role of explainability in AI, emphasizing the need for relevant context in decision-making. Ghani discusses data-driven strategies from political campaigns and the ethical challenges in predictive modeling. He highlights the importance of trust and feedback mechanisms to improve model transparency, particularly in sensitive areas like healthcare and public safety.
Jul 15, 2019 • 26min
Inspiring New Machine Learning Platforms w/ Bioelectric Computation with Michael Levin - TWiML Talk #282
Michael Levin, a professor of biology and director at the Allen Discovery Center, explores groundbreaking concepts in bioelectric computation and machine learning. He discusses how synthetic living machines can revolutionize AI architectures. Levin emphasizes the role of bioelectric processes in regeneration, revealing that DNA isn't the only player in shaping organism behavior. The conversation also touches on the potential of bioelectric medicine for transformative treatments in regenerative health and the intriguing parallels between biological systems and AI.
Jul 9, 2019 • 41min
Simulation and Synthetic Data for Computer Vision with Batu Arisoy - TWiML Talk #281
In this engaging discussion, Batu Arisoy, a Research Manager at Siemens Corporate Technology, shares insights from his work on limited-data computer vision problems. He highlights innovative approaches to generating synthetic data, aiding object recognition for tasks like train maintenance. Batu also discusses collaborative workshops tackling class imbalances in computer vision, and a groundbreaking AI-user collaboration model with the Office of Naval Research that integrates natural language processing. Tune in for fascinating breakthroughs that blend AI, simulation, and user intent!
Jul 8, 2019 • 53min
Spiking Neural Nets and ML as a Systems Challenge with Jeff Gehlhaar - TWIML Talk #280
Jeff Gehlhaar, VP of Technology and Head of AI Software Platforms at Qualcomm, dives into the world of AI and machine learning. He shares his journey from engineering to leading AI innovations, focusing on spiking neural networks that mimic biological processes. The discussion highlights Qualcomm's advancements in AI software development, the role of federated learning in enhancing privacy, and the importance of interoperability among frameworks like ONNX. Gehlhaar emphasizes a holistic approach to AI, integrating hardware and algorithms for future innovations.
Jul 1, 2019 • 46min
Transforming Oil & Gas with AI with Adi Bhashyam and Daniel Jeavons - TWIML Talk #279
Join Daniel Jeavons, General Manager of Data Science at Shell, and Adi Bhashyam, VP at C3 AI, as they dive into the transformative power of AI in the oil and gas industry. They discuss advancements in Shell's AI platforms, the complexities of data replication, and the challenges of scaling machine learning solutions across multiple sites. The conversation also highlights a new reward engine aimed at enhancing customer experiences and the innovative use of machine learning in optimizing energy production while addressing environmental concerns.
Jun 27, 2019 • 39min
Fast Radio Burst Pulse Detection with Gerry Zhang - TWIML Talk #278
Yunfan Gerry Zhang, a PhD student at UC Berkeley and SETI research center affiliate, dives into the fascinating intersection of machine learning and astrophysics. He discusses his groundbreaking paper on detecting fast radio bursts using innovative techniques. Highlights include the use of Generative Adversarial Networks for predicting cosmic signals and the challenges of processing immense astronomical datasets. Gerry also shares insights on detecting periodicity in signals and the transformative impact of AI in analyzing radio frequency data.
Jun 24, 2019 • 42min
Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277
In this conversation, Laurence Watson, Co-Founder and CTO of Plentiful Energy and former data scientist at Carbon Tracker, dives into innovative methods for tracking CO2 emissions using machine learning and satellite imagery. He shares insights from Carbon Tracker's research on fossil fuel power plants and discusses the challenges of quantifying emissions accurately. The talk also highlights advancements in cloud solutions for data integration and how they enhance monitoring efforts, making environmental data more accessible and actionable.
