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, 2021 • 51min
Constraint Active Search for Human-in-the-Loop Optimization with Gustavo Malkomes - #505
Gustavo Malkomes, a research engineer at Intel with expertise in active learning and multi-objective optimization, dives into an innovative algorithm for multiobjective experimental design. He discusses how his work allows teams to explore multiple metrics simultaneously and efficiently, enhancing human-in-the-loop optimization. The conversation covers the balance between competing goals, the significance of stable solutions, and the fascinating applications of his research in real-world scenarios, such as optimization and drug discovery.
Jul 26, 2021 • 37min
Fairness and Robustness in Federated Learning with Virginia Smith -#504
Virginia Smith, an assistant professor at Carnegie Mellon University, delves into her innovative work on federated learning. She discusses her research on fairness and robustness, highlighting the challenges of maintaining model performance across diverse data inputs. The conversation touches on her findings from the paper 'Ditto', exploring the trade-offs in AI ethics. Additionally, she shares insights on leveraging data heterogeneity in federated clustering to enhance model effectiveness and the balance between privacy and robust learning.
Jul 22, 2021 • 41min
Scaling AI at H&M Group with Errol Koolmeister - #503
Errol Koolmeister, head of AI Foundation at H&M Group, shares insights on the fashion retail giant's transformative AI journey. He discusses implementing AI for fashion forecasting and pricing, emphasizing the significance of data accessibility and stakeholder engagement. Highlighting the challenges of scaling AI, Errol explains the importance of balancing simplicity with complexity in modeling. He also addresses managing AI initiatives within a large organization, focusing on building a robust infrastructure and fostering an 'AI-first' culture.
Jul 19, 2021 • 49min
Evolving AI Systems Gracefully with Stefano Soatto - #502
Stefano Soatto, VP of AI Application Science at AWS and a professor at UCLA, dives into the fascinating world of Graceful AI. He discusses the challenges of evolving AI in real-world applications while avoiding the pitfalls of constant retraining. Topics include the critical timing of regularization in deep learning, the parallels between model compression and material science, and the intricacies of model reliability. Stefano also unpacks innovations like focal distillation and their potential to enhance lifelong learning in AI systems.
Jul 15, 2021 • 45min
ML Innovation in Healthcare with Suchi Saria - #501
In this engaging discussion, Suchi Saria, Founder and CEO of Bayesian Health and an esteemed professor at Johns Hopkins University, shares her journey at the intersection of machine learning and healthcare. She highlights the slow acceptance of AI in medical practice and discusses pockets of success in the field. Saria elaborates on groundbreaking advancements in sepsis detection and the challenges of integrating ML tools into clinical workflows. Finally, she envisions a future where improved data accessibility drives better patient outcomes in healthcare.
12 snips
Jul 12, 2021 • 42min
Cross-Device AI Acceleration, Compilation & Execution with Jeff Gehlhaar - #500
Jeff Gehlhaar, VP of Technology at Qualcomm, dives into the world of AI compilers and their importance in managing parallelism. He highlights Qualcomm's latest innovations, including AI Engine Direct, which bridges capabilities across devices. The conversation covers how research on compression and quantization is translated into real products and the competitive landscape of ML compilers like Glow and TVM. Additionally, Jeff discusses advancements in benchmarking and the integration of AI frameworks that enhance smartphone performance.
Jul 8, 2021 • 49min
The Future of Human-Machine Interaction with Dan Bohus and Siddhartha Sen - #499
Dan Bohus is a senior principal researcher at Microsoft, specializing in human-computer interaction, while Siddhartha Sen focuses on the collaboration between AI and human design. They discuss how projects like Maia Chess and Situated Interaction are redefining human-AI interaction. The conversation covers the challenges of AI understanding human behavior, the integration of natural language processing in chess, and the importance of embodying social cues in machines. Both guests share their excitement for future innovations and the potential for enhanced collaboration between humans and AI.
Jul 5, 2021 • 41min
Vector Quantization for NN Compression with Julieta Martinez - #498
Julieta Martinez, a senior research scientist at Waabi, dives into the fascinating world of AI and self-driving technology. She highlights how insights from large-scale visual search can bolster neural network compression techniques. The conversation also covers the intricacies of using product quantization to enhance performance while managing vast datasets. Additionally, Julieta discusses her research on deep multitask learning, demonstrating how integrating localization, perception, and prediction can revolutionize autonomous systems and improve real-world applications.
7 snips
Jul 1, 2021 • 42min
Deep Unsupervised Learning for Climate Informatics with Claire Monteleoni - #497
Claire Monteleoni, an associate professor at the University of Colorado Boulder, shares her inspiring journey from environmental activism to a leading role in climate informatics. The discussion covers innovative machine learning techniques for analyzing climate data, particularly unsupervised methods for downscaling. Claire also highlights the evolution of climate informatics conferences and their focus on collaboration. Additionally, she emphasizes the need for integrating social justice in climate action, advocating for resilience in vulnerable communities.
Jun 28, 2021 • 48min
Skip-Convolutions for Efficient Video Processing with Amir Habibian - #496
In this engaging discussion, Amir Habibian, a Senior Staff Engineer Manager at Qualcomm Technologies, delves into groundbreaking advancements in video processing. He explores the innovative concept of skip convolutions, which enhance efficiency in visual neural networks. Amir also introduces his FrameExit framework, a conditional early exiting mechanism for video recognition, optimizing how frames are processed. The conversation highlights the future of AI in video technology and the importance of tailoring methods to maximize performance.
