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
May 30, 2019 • 44min
Snorkel: A System for Fast Training Data Creation with Alex Ratner - TWiML Talk #270
In this discussion, Alex Ratner, a Ph.D. student at Stanford and creator of Snorkel, dives into revolutionary data labeling techniques. He explains how Snorkel simplifies the creation of training data using weak supervised learning, transforming traditional methods. Ratner shares real-world applications, including collaborations with companies like Google. The conversation also addresses the complexities of labeling functions, the influence of human biases in machine learning, and exciting future advancements like Snorkel Metal for multitask learning.
May 28, 2019 • 48min
Advancing Autonomous Vehicle Development Using Distributed Deep Learning with Adrien Gaidon - TWiML Talk #269
Adrien Gaidon, Machine Learning Lead at Toyota Research Institute, shares his journey into distributed deep learning for autonomous vehicles. He dives into the evolution of TRI's platform and the pivotal role of data simulation in this field. Gaidon discusses the complexities of building infrastructure for large datasets and GPU management, as well as the integration of PyTorch and Horovod. He highlights advancements in model compression and multitask learning, emphasizing their importance for efficient self-driving technology.
May 23, 2019 • 50min
Are We Being Honest About How Difficult AI Really Is? w/ David Ferrucci - TWiML Talk #268
David Ferrucci, Founder and CEO of Elemental Cognition and former leader of the IBM Watson team, dives into the complexities of AI development. He discusses the crucial role of human-like understanding in AI and the significant investments needed to reach even modest milestones. Ferrucci shares insights on the evolution of perceptions around AI, the power of hybrid systems, and the importance of transparency in AI decision-making. His journey from Watson's creation to current challenges highlights the need for robust metrics and diverse teams in AI development.
May 20, 2019 • 1h 3min
Gauge Equivariant CNNs, Generative Models, and the Future of AI with Max Welling - TWiML Talk #267
In this enlightening discussion, Max Welling, a research chair in machine learning at the University of Amsterdam and Qualcomm's VP of Technologies, dives into groundbreaking topics. He reveals his work on Bayesian deep learning, Gauge Equivariant CNNs, and innovations in AI for improved computing efficiency. Max also shares his insights on the evolution of AI, emphasizing the balance between models and data, and explores the exciting possibilities of integrating generative models with rule-based systems to pave the way for artificial general intelligence.
May 16, 2019 • 43min
Can We Trust Scientific Discoveries Made Using Machine Learning? with Genevera Allen - TWiML Talk #266
Genevera Allen, an associate professor of statistics at Rice University, shares her insights on trust in machine learning discoveries. She discusses the challenges of reproducibility in scientific research, especially in biomedical fields. Genevera reflects on her impactful talk at the AAAS conference, addressing audience reactions and future research directions. The conversation also emphasizes the importance of statistical methods in validating results and the need for better education and terminology in the application of machine learning to scientific research.
May 13, 2019 • 38min
Creative Adversarial Networks for Art Generation with Ahmed Elgammal - TWiML Talk #265
Join Ahmed Elgammal, a Rutgers University professor and director of the Art and Artificial Intelligence Lab, as he takes us through the fascinating world of AI-generated art. Discover the innovative AICAN project, which creates original portraits using a blend of AI and centuries of artistic tradition. Elgammal discusses the delicate balance of aesthetics in Generative Adversarial Networks and how AI mirrors the evolution of artistic styles. Dive into the future of creativity, where machines collaborate with human artists to redefine artistic boundaries!
May 10, 2019 • 42min
Diagnostic Visualization for Machine Learning with YellowBrick w/ Rebecca Bilbro - TWiML Talk #264
Rebecca Bilbro, Head of Data Science at ICX Media and co-creator of the YellowBrick visualization library, shares her fascinating journey in toolmaking. She discusses how YellowBrick enhances machine learning visualization and its innovative applications, including natural language processing. Listeners will learn about the significance of part of speech ratios in categorizing document types and how classification techniques can bolster regression analysis. Bilbro also emphasizes the role of visual tools in model selection and performance tracking.
May 9, 2019 • 38min
Librosa: Audio and Music Processing in Python with Brian McFee - TWiML Talk #263
Brian McFee, an assistant professor at NYU and the creator of the Librosa library, shares his journey in music technology and data science. He discusses the core functions of Librosa for audio processing, the challenges of beat tracking in music, and his experience developing a jazz search engine. McFee also highlights workflows for audio analysis using Python, showcasing essential tools like Fast Fourier Transforms and visualization techniques. His insights aim to make audio analysis more accessible and insightful for developers.
May 7, 2019 • 49min
Practical Natural Language Processing with spaCy and Prodigy w/ Ines Montani - TWiML Talk #262
Ines Montani, co-founder of Explosion and lead developer of spaCy and Prodigy, dives into the world of natural language processing. She shares insights on the journey of developing spaCy as an accessible NLP tool for industry. They discuss the importance of community contributions, the balance between open-source and commercial products, and advancements like transfer learning. Ines highlights lessons learned from project failures and the significance of validating ideas through user experience, all while maintaining a resilient team culture.
May 6, 2019 • 34min
Scaling Jupyter Notebooks with Luciano Resende - TWiML Talk #261
Luciano Resende, an Open Source AI Platform Architect at IBM, dives into the world of Jupyter Notebooks and scaling challenges. He discusses the evolution of JupyterHub and Enterprise Gateway, emphasizing their roles in data science and multi-user environments. The conversation touches on enhancing collaboration through better integration with Git and shared file systems. Luciano shares success stories from IBM Watson Studio and PayPal, and highlights exciting developments planned for the next version of Enterprise Gateway, focusing on Kubernetes optimization.
