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
Aug 31, 2020 • 43min
How Machine Learning Powers On-Demand Logistics at Doordash with Gary Ren - #405
Gary Ren, a machine learning engineer at DoorDash, dives into the transformative role of machine learning in logistics. He shares insights on optimizing route planning and balancing the three-sided marketplace of consumers, dashers, and merchants. The conversation highlights the integration of predictive modeling for delivery timings and the innovative use of reinforcement learning to boost efficiency. Plus, Ren discusses challenges in unpredictable environments, including how to adapt to real-time conditions to improve customer satisfaction.
8 snips
Aug 27, 2020 • 45min
Machine Learning as a Software Engineering Discipline with Dillon Erb - #404
Dillon Erb, Co-founder and CEO of Paperspace, discusses how to tackle the challenges of building scalable machine learning workflows. He emphasizes the importance of integrating software engineering principles into machine learning, focusing on reproducibility and effective workflow management. Dillon also highlights how MLOps platforms can assist developers, and explores the relationship between Gradient and Kubeflow. Additionally, he touches on innovations in machine learning visualization that enhance practical applications across various industries.
Aug 24, 2020 • 53min
AI and the Responsible Data Economy with Dawn Song - #403
Dawn Song, a Professor of Computer Science at UC Berkeley and CEO of Oasis Labs, dives into the future of data privacy and security. She discusses creating a responsible data economy that empowers users while leveraging techniques like blockchain and differential privacy. The conversation highlights the risks of adversarial attacks on AI, and how innovations in homomorphic encryption can secure sensitive data. Dawn also shares insights on balancing privacy with effective COVID-19 contact tracing, emphasizing the importance of technology in protecting personal information.
Aug 20, 2020 • 41min
Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka Carvalho - #402
In a fascinating discussion, Wilka Carvalho, a PhD student at the University of Michigan, delves into his research on AI agents designed for completing household tasks. He explores the challenges of object interaction and how his Relational Object Model Learning Agent (ROMA) tackles these issues. Carvalho emphasizes the importance of representation learning and real-world data in creating effective agents. He also shares insights on achieving high sample efficiency and the methodologies for training robotic agents in complex environments.
Aug 17, 2020 • 1h 27min
Model Explainability Forum - #401
Join a stellar panel featuring Raid Ghani from Carnegie Mellon, Solon Barrokas of Cornell and Microsoft, IBM's Kush Varshney, startup CEO Alyssa Labgenova, and Harvard's Hima Lakaraju. They tackle pressing issues in the realm of model explainability. Discussions dive into stakeholder-driven approaches, counterfactual explanations, and the impact of legal frameworks on automated decision-making. The experts also highlight vulnerabilities in AI explanations and the critical need for trust and fairness, emphasizing collaboration to enhance understanding and improve outcomes.
Aug 13, 2020 • 59min
What NLP Tells Us About COVID-19 and Mental Health with Johannes Eichstaedt - #400
In this conversation with Johannes Eichstaedt, an Assistant Professor of Psychology at Stanford University, they explore how he blends physics and psychology to analyze mental health trends using big data. Johannes discusses the fascinating use of Twitter data to uncover psychological impacts during COVID-19, revealing insights into societal behavior changes and mental health fluctuations. He also highlights the challenges of capturing nuanced language variations across different communities, shedding light on the dynamic nature of social norms during the pandemic.
Aug 10, 2020 • 45min
Human-AI Collaboration for Creativity with Devi Parikh - #399
Devi Parikh, an Associate Professor at Georgia Tech and research scientist at Facebook AI Research, dives into the fascinating intersection of AI and creativity. She shares her insights on how AI can enhance the creative process for artists. From discussing the nuances of creativity to exploring innovative tools like casual creation for art generation, she highlights how AI can foster collaboration and inspire unique artistic expressions. Devi also touches on transforming personal journaling into abstract visuals, showcasing the potential of AI in everyday creativity.
Aug 6, 2020 • 49min
Neural Augmentation for Wireless Communication with Max Welling - #398
In this engaging conversation, Max Welling, Vice President of Technologies at Qualcomm Netherlands and Professor at the University of Amsterdam, delves into neural augmentation and its real-world applications. He discusses federated learning as a means to enhance data privacy for users, while exploring the exciting intersection of quantum mechanics and neural networks. Max also highlights innovative chip design approaches that merge traditional engineering with machine learning, showcasing the potential of these advancements in tackling complex challenges.
Aug 4, 2020 • 1h
Quantum Machine Learning: The Next Frontier? with Iordanis Kerenidis - #397
Iordanis Kerenidis, a Research Director at CNRS Paris and Head of Quantum Algorithms at QC Ware, discusses the groundbreaking realm of quantum machine learning. He shares insights from his keynote at ICML, delving into the evolution of quantum algorithms and their historical milestones. The conversation navigates the intricacies of quantum computing fundamentals, showcasing the power of superposition and its applications in recommendation systems. Iordanis also tackles challenges in integrating quantum methods with classical techniques, revealing the exciting potential and complexities ahead.
Jul 30, 2020 • 47min
ML and Epidemiology with Elaine Nsoesie - #396
Elaine Nsoesie, an assistant professor of global health at Boston University, brings her expertise in machine learning and epidemiology to discuss innovative approaches in public health. She delves into how data from social media and search engines can track health behaviors, particularly in African countries. The conversation also highlights the application of satellite imagery to assess obesity rates and the challenges faced by epidemiologists during the COVID-19 pandemic, focusing on health disparities among marginalized communities.
