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.
\n\nHighlights from the discussion include:
\n\nThe conversation concludes with a forward-looking exploration of opportunities in government, education, and healthcare, and Gabriel’s optimism about building ecosystems where startups and local talent thrive.
\n\n🎧 Tune in to learn from Gabriel’s thoughtful perspectives on navigating the complexities of building data-driven cultures, the global AI landscape, and how to leverage data for impactful change.
\n\nYou can find more on our website: https://high-signal.delphina.ai/
","summary":"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.","date_published":"2024-11-20T16:00:00.000-05:00","attachments":[{"url":"https://aphid.fireside.fm/d/1437767933/7dfbb66c-ee57-4196-9f73-43348bd083a5/ca3782d4-c7a4-44d6-a7c3-176201c14f69.mp3","mime_type":"audio/mpeg","size_in_bytes":121731903,"duration_in_seconds":3726}]},{"id":"1dedb130-8a6b-4a8d-890a-8d8b41cbd651","title":"Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong","url":"https://highsignal.fireside.fm/4","content_text":"Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.\n\nRamesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the risk aversion trap, the importance of learning from negative results, and how generative AI is reshaping the experimentation landscape.\n\nWe also talk about common failure modes and the types of things you're probably doing wrong, along with strategies to avoid these pitfalls. Plus, we discussed the role of incentives, the necessity of data driven decision making, and what it means to experiment in high stakes environments.","content_html":"Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.
\n\nRamesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the risk aversion trap, the importance of learning from negative results, and how generative AI is reshaping the experimentation landscape.
\n\nWe also talk about common failure modes and the types of things you're probably doing wrong, along with strategies to avoid these pitfalls. Plus, we discussed the role of incentives, the necessity of data driven decision making, and what it means to experiment in high stakes environments.
","summary":"Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.","date_published":"2024-11-07T07:00:00.000-05:00","attachments":[{"url":"https://aphid.fireside.fm/d/1437767933/7dfbb66c-ee57-4196-9f73-43348bd083a5/1dedb130-8a6b-4a8d-890a-8d8b41cbd651.mp3","mime_type":"audio/mpeg","size_in_bytes":49230246,"duration_in_seconds":3076}]},{"id":"c6ce415b-4f49-41ae-b3db-700040f0674d","title":"Episode 3: Data Science Meets Management: Teamwork, Experimentation, and Decision-Making","url":"https://highsignal.fireside.fm/3","content_text":"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.","content_html":"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.
","summary":"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.","date_published":"2024-10-19T12:00:00.000-04:00","attachments":[{"url":"https://aphid.fireside.fm/d/1437767933/7dfbb66c-ee57-4196-9f73-43348bd083a5/c6ce415b-4f49-41ae-b3db-700040f0674d.mp3","mime_type":"audio/mpeg","size_in_bytes":50126181,"duration_in_seconds":3132}]},{"id":"44cfa4bc-192f-4325-90d2-13b7b9e1d781","title":"Episode 2: Fooling Yourself Less: The Art of Statistical Thinking in AI","url":"https://highsignal.fireside.fm/2","content_text":"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.","content_html":"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.
","summary":"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.","date_published":"2024-10-19T11:00:00.000-04:00","attachments":[{"url":"https://aphid.fireside.fm/d/1437767933/7dfbb66c-ee57-4196-9f73-43348bd083a5/44cfa4bc-192f-4325-90d2-13b7b9e1d781.mp3","mime_type":"audio/mpeg","size_in_bytes":58426015,"duration_in_seconds":3651}]},{"id":"c4068f54-90b5-4e7a-b036-07a08ac9e813","title":"Episode 1: The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale","url":"https://highsignal.fireside.fm/1","content_text":"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.","content_html":"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.
","summary":"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.","date_published":"2024-10-19T09:00:00.000-04:00","attachments":[{"url":"https://aphid.fireside.fm/d/1437767933/7dfbb66c-ee57-4196-9f73-43348bd083a5/c4068f54-90b5-4e7a-b036-07a08ac9e813.mp3","mime_type":"audio/mpeg","size_in_bytes":72201950,"duration_in_seconds":4512}]}]}