High Signal

Episode Archive

Episode Archive

5 episodes of High Signal since the first episode, which aired on October 19th, 2024.

  • Episode 5: The Hard Truth About Building AI Systems and What Most Leaders Miss About AI

    November 20th, 2024  |  1 hr 2 mins
    ai, data science, machine learning

    In this episode of High Signal, Gabriel Weintraub (the Amman Professor of Operations, Information, and Technology at Stanford Graduate School of Business), brings his expertise in market design, data science, and operations, enriched by his experience with global platforms like Uber and Mercado Libre, to a conversation that spans practical strategies, cultural insights, and global perspectives on data and AI.

  • Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong

    November 7th, 2024  |  51 mins 16 secs

    Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.

  • Episode 3: Data Science Meets Management: Teamwork, Experimentation, and Decision-Making

    October 19th, 2024  |  52 mins 12 secs

    Chiara Farronato (Harvard Business School) discusses how digital platforms like Airbnb and Uber have transformed industries. She explores the challenges of fostering collaboration between managers and data scientists, bridging communication gaps, and building data-driven cultures. Chiara also delves into the complexities of managing peer-to-peer marketplaces and the evolving role of data in decision-making. This episode offers key insights for business leaders working with technical teams and navigating platform-based innovation.

  • Episode 2: Fooling Yourself Less: The Art of Statistical Thinking in AI

    October 19th, 2024  |  1 hr 51 secs

    Hugo Bowne-Anderson welcomes Andrew Gelman, professor at Columbia University, to discuss the practical side of statistics and data science. They explore the importance of high-quality data, computational skills, and using simulation to avoid misleading results. Andrew dives into real-world applications like election predictions and highlights causal inference’s critical role in decision-making. This episode offers insights into balancing statistical theory with applied data analysis, making it a must-listen for both data practitioners and those interested in how statistics shapes our world.

  • Episode 1: The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale

    October 19th, 2024  |  1 hr 15 mins

    Michael Jordan (UC Berkeley) on the future of machine learning as it extends to a planetary scale in "The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale." In this episode, Mike speaks with Hugo about the evolution of AI, the importance of integrating machine learning, computer science, and economics, and how AI can scale to address planetary-level challenges.