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
4 snips
Jan 6, 2020 • 50min
Trends in Fairness and AI Ethics with Timnit Gebru - #336
Timnit Gebru, a research scientist at Google Brain and co-lead of their ethical AI team, dives into the evolving landscape of AI fairness and ethics. She discusses the importance of representation, highlighting initiatives like Black in AI that enhance diversity in tech conferences. Gebru also reflects on the significance of intersectional testing and the introduction of model cards for transparency. With insights from NeurIPS, she navigates the challenges of promoting ethical AI amidst personal and institutional hurdles, underscoring the need for inclusive voices in shaping AI governance.
Jan 2, 2020 • 1h 8min
Trends in Reinforcement Learning with Chelsea Finn - #335
Chelsea Finn, Assistant Professor at Stanford University, shares her insights on advancements in reinforcement learning. She breaks down model-based approaches and the challenges of exploration in complex environments like Montezuma's Revenge. The discussion also touches on the importance of curriculum learning in robotics and the nuances of batch off-policy learning. With exciting implications for real-world applications, Chelsea highlights the evolving landscape of RL libraries and their role in bridging the gap between simulation and practical deployment.
Dec 30, 2019 • 1h 20min
Trends in Machine Learning & Deep Learning with Zack Lipton - #334
In this engaging discussion, Zack Lipton, a Professor at CMU with expertise in machine learning, explores key advances from 2019 in the field. He delves into the evolution of deep learning, noting the impact of models like BERT and challenges related to distribution shifts. Lipton also discusses innovative approaches in causal inference and fairness, advocating for continued research on model robustness. Lastly, he shares predictions about commodification in AI and the need for inclusive participation in the future landscape of machine learning.
Dec 27, 2019 • 40min
FaciesNet & Machine Learning Applications in Energy with Mohamed Sidahmed - #333
Join Mohamed Sidahmed, R&D Manager at Shell, as he discusses groundbreaking advancements in machine learning and AI at NeurIPS. He dives into the innovative FaciesNet architecture, which transforms geological data into spectrograms for improved rock facies classification. Learn how these techniques revolutionize seismic imaging and enhance predictive capabilities, ultimately boosting hydrocarbon exploration confidence. Sidahmed also highlights the vital role of collaboration between academia and industry in driving energy-related AI innovations.
Dec 26, 2019 • 43min
Machine Learning: A New Approach to Drug Discovery with Daphne Koller - #332
Daphne Koller, the co-founder of Coursera and CEO of Insitro, shares her expertise on the revolutionary role of machine learning in drug discovery. She discusses the hurdles of the pharmaceutical landscape, including high costs and regulatory challenges. Koller emphasizes how ML can streamline decision-making and enhance drug efficacy through targeted therapies. Highlighting innovative techniques like CRISPR and high throughput biology, she stresses the need for collaboration between biology and tech experts to transform healthcare.
Dec 24, 2019 • 40min
Sensory Prediction Error Signals in the Neocortex with Blake Richards - #331
Blake Richards, Assistant Professor at McGill University and Core Faculty Member at Mila, dives into the brain's learning abilities with a focus on sensory prediction error signals. He elaborates on two-photon calcium imaging studies revealing how the neocortex processes unexpected stimuli. Discussing predictive coding, he highlights its implications for both neuroscience and machine learning. The conversation also touches on integrating memory systems in reinforcement learning, showcasing how insights from biology can lead to more adaptive AI.
Dec 23, 2019 • 53min
How to Know with Celeste Kidd - #330
In a captivating discussion, Celeste Kidd, an Assistant Professor of Psychology at UC Berkeley, explores how we form beliefs and our curiosity about the world. She explains the role of past experiences in shaping future interests and how certainty can lead to rigidity in thought. The conversation also delves into the interplay between attention, decision-making, and how infants develop probabilistic expectations. Kidd's insights reveal the complexities of knowledge acquisition and the implications for both individuals and intelligent systems.
Dec 20, 2019 • 51min
Using Deep Learning to Predict Wildfires with Feng Yan - #329
Feng Yan, an Assistant Professor at the University of Nevada, Reno, is at the forefront of using machine learning for wildfire prediction. He introduces ALERTWildfire, a network of cameras that capture real-time data to enhance monitoring efforts. The conversation dives into innovative camera deployments, the integration of satellite and ground-level data, and overcoming challenges in model training. Feng also discusses leveraging IaaS and FaaS for scalability and cost-effectiveness in tackling the growing threat of wildfires.
Dec 19, 2019 • 47min
Advancing Machine Learning at Capital One with Dave Castillo - #328
In this discussion, Dave Castillo, Managing VP for ML at Capital One, shares his journey from creating early ML systems at NASA to leading ML adoption at a major financial institution. He highlights the shift from lab-based ML to enterprise-wide integration and discusses innovative use cases. Dave introduces a new role that combines product management and design thinking, aimed at enhancing user experience. He also addresses the challenges of model risk documentation, automation opportunities, and the evolving skill sets required in data science and ML roles.
Dec 17, 2019 • 38min
Helping Fish Farmers Feed the World with Deep Learning w/ Bryton Shang - #327
Bryton Shang, Founder and CEO of Aquabyte, is pioneering the integration of computer vision in fish farming. He discusses the challenges of measuring fish health underwater and how AI can revolutionize operations. Fascinating insights include the development of fish facial recognition for health tracking and innovative camera tech to tackle sea lice issues. Bryton shares his journey from academia to entrepreneurship, emphasizing the need for sustainable and efficient aquaculture practices to help feed the world.
