Past episodes listed in reverse chronological order. We have high-quality transcripts for a few episodes (see here).
2020
Arun Verma → How machine learning is being used in quantitative finance
Harish Doddi → Understanding machine learning model governance
Wes McKinney → Improving performance and scalability of data science libraries
Pete Warden → Why TinyML will be huge
Evan Sparks → An open source platform for training deep learning models
Kenneth Stanley → Algorithms that continually invent both problems and solutions
Bruno Gonçalves → Computational Models and Simulations of Epidemic Infectious Diseases
Robert Munro → Human-in-the-loop machine learning
Chris Nicholson → Next-generation simulation software will incorporate deep reinforcement learning
Solmaz Shahalizadeh → Business at the speed of AI: Lessons from Shopify
Edo Liberty → How deep learning is being used in search and information retrieval
Alejandro Saucedo → The responsible development, deployment and operation of machine learning systems
Edmon Begoli → Hyperscaling natural language processing
Krishna Gade → What businesses need to know about model explainability
Dean Wampler → Scalable Machine Learning, Scalable Python, For Everyone
Dafna Shahaf → Computational humanness, analogy and innovation, and soft concepts
David Talby → Building domain specific natural language applications
Morten Dahl → The state of privacy-preserving machine learning
Sijie Guo → Taking messaging and data ingestion systems to the next level
Bahman Bahmani → Business at the speed of AI: Lessons from Rakuten
2019
Ben and Mikio Braun → Key AI and Data Trends for 2020
Rajat Monga → The evolution of TensorFlow and of machine learning infrastructure
Reza Zadeh → Building large-scale, real-time computer vision applications
Paco Nathan → Taking stock of foundational tools for analytics and machine learning