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
Jun 20, 2019 • 45min
Topic Modeling for Customer Insights at USAA with William Fehlman - TWIML Talk #276
William Fehlman, Director of Data Science at USAA, shares his expertise in topic modeling and natural language processing. He explains how USAA leverages these techniques to enhance customer service by analyzing both structured and unstructured data from communication channels. Fehlman delves into methodologies like latent semantic indexing and non-negative matrix factorization, discussing their effectiveness in uncovering customer insights and optimizing operational strategies. Insights on coherence scoring and term frequency provide a deeper understanding of the topic modeling process.
Jun 18, 2019 • 44min
Phronesis of AI in Radiology with Judy Gichoya - TWIML Talk #275
Judy Gichoya, an interventional radiology fellow and co-organizer of Black in AI, shares her insights on the interplay of AI and radiology. She examines the claims of superhuman AI, emphasizing its true potential in enhancing radiological diagnostics. Judy humorously debunks the myth of AI replacing radiologists, calling for collaboration rather than competition. The conversation dives into the biases that can skew AI performance and the need for practical education to effectively integrate AI within the field.
Jun 14, 2019 • 43min
The Ethics of AI-Enabled Surveillance with Karen Levy - TWIML Talk #274
In this engaging conversation with Karen Levy, an assistant professor at Cornell University, the focus is on the ethics of AI-enabled surveillance. She highlights how surveillance technology can disproportionately affect marginalized groups, especially truck drivers, whose dignity and autonomy are compromised by constant monitoring. Karen advocates for a critical perspective on AI, emphasizing that technology should enhance, rather than undermine, quality of life. The discussion encourages directly engaging with affected communities to grasp the nuanced impacts of these systems.
Jun 11, 2019 • 46min
Supporting Rapid Model Development at Two Sigma with Matt Adereth & Scott Clark - TWIML Talk #273
In this engaging discussion, Matt Adereth, Managing Director at Two Sigma, and Scott Clark, CEO of SigOpt, dive into the complexities of model development in finance. They explore Two Sigma's innovative end-to-end modeling platform and the challenges of production. The conversation highlights how optimization and experimentation tools like SigOpt can transform machine learning processes. The speakers also discuss the motivation behind companies adopting automation, the significance of domain expertise, and the ongoing evolution of programming languages in data science.
Jun 6, 2019 • 42min
Scaling Model Training with Kubernetes at Stripe with Kelley Rivoire - TWIML Talk #272
Kelley Rivoire, an engineering manager at Stripe with expertise in machine learning infrastructure, shares her insights on scaling model training. She discusses Stripe's journey from production-focused systems to building the Railyard API for efficient model management on Kubernetes. Kelley highlights the importance of collaboration across teams, custom parameters for hyperparameter optimization, and the significance of an infrastructure team to support machine learning advancements. Tune in to discover how Stripe is navigating the complexities of AI implementation!
Jun 3, 2019 • 46min
Productizing ML at Scale at Twitter with Yi Zhuang - TWIML Talk #271
In this enlightening conversation, Yi Zhuang, a Senior Staff Engineer at Twitter, shares his insights from leading the machine learning core environment on the Cortex team. He discusses the evolution of Twitter's machine learning landscape and the role of the DeepBird framework, which integrates TensorFlow for enhanced model training. Zhuang also highlights the newly formed 'Meta' team focused on bias, fairness, and accountability in algorithms, stressing the importance of ethical AI practices amid technological advancements.
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.
