Best Delphina Podcasts (2025)

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Episode 26: Gen AI's True Cost: Why Today's Wins Are Tomorrow's Debts 43:14

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13d ago43:14

43:14

Vishnu Ram Venkataraman (Generative AI Executive & Entrepreneur; former AI Leader at Credit Karma and Intuit) joins High Signal to unpack the true cost of generative AI. Having scaled AI solutions impacting over 140 million users, Vishnu reveals why the ease of shipping Gen AI prototypes often masks significant operational and engineering debts, ch…

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Episode 25: How Data-Driven Growth Redefined a Media Giant 56:22

26d ago56:22

56:22

Sergey Fogelson (VP of Data Science, Televisa Univision) joins High Signal to reveal how the world’s largest Spanish-language media company built a sophisticated data engine from the ground up. This transformation fueled a tenfold expansion of its digital streaming business by redefining how the company connects with 300 million viewers worldwide. …

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Episode 24: Rebuilding an Airline for the 21st Century: LATAM's Data-Driven Transformation 49:56

1M ago49:56

49:56

Andrés Bucchi (Chief Data Officer, LATAM Airlines) joins High Signal to unpack how a century-old airline reinvented itself with data and AI—and how that transformation is unlocking value from fuel efficiency to fraud detection. LATAM has built a massive data operation, experimenting across everything from pricing to operations, while customers bene…

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Episode 23: Why Most AI Agents Fail (and What It Takes to Reach Production) 51:17

2M ago51:17

51:17

Anu Bharadwaj (President, Atlassian) joins High Signal to unpack how humans and AI agents will work together across the enterprise, and how that shift could change the very nature of teamwork. Atlassian employees have already built thousands of agents across product, marketing, engineering, and HR teams, while customers like HarperCollins are cutti…

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Episode 22: Why a Trillion Dollars of Market Cap Is Up for Grabs (and How AI Teams Will Win It) 46:50

2M ago46:50

46:50

Tomasz Tunguz (Theory Ventures) joins High Signal to unpack why a trillion dollars of market cap is up for grabs as AI reshapes enterprise software. He explains why workflows are now changing faster than packaged software can keep up, how “liquid software” is redefining CRM and marketing automation, and why background agents will require a new kind…

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Episode 21: Why Great Data Still Leads to Bad Decisions (And How to Fix It) 50:38

3M ago50:38

50:38

Amy Edmondson (Harvard Business School) and Mike Luca (Johns Hopkins) join High Signal to unpack what actually drives good decisions in data‑rich organizations. Using contrasts like the Bay of Pigs vs. the Cuban Missile Crisis and product cases such as Airbnb’s work on measuring discrimination, they show how decision quality tracks conversation qua…

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Episode 20: Incentives, Accountability, and the Data Leader’s Dilemma 1:03:13

3M ago1:03:13

1:03:13

Daragh Sibley, Chief Algorithms Officer at Literati and former Director of Data Science at Stitch Fix, joins High Signal to unpack how machine-learning moves from slide-deck promise to bottom-line impact. He walks through his shift from academic research on how kids learn to read to owning inventory and personalization algorithms that decide which …

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Episode 19: Defaults, Decisions, and Dynamic Systems: Behavioral Science Meets AI 54:08

4M ago54:08

54:08

Lis Costa, Chief of Innovation and Partnerships at the Behavioural Insights Team, joins High Signal to explore how behavioral science is reshaping public policy, digital platforms, and machine learning. She explains how defaults influence behavior at scale, why personalization and chatbots are unlocking new kinds of interventions, and what happens …

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Episode 18: High-Stakes AI Systems and the Cost of Getting It Wrong 58:45

4M ago58:45

58:45

Sudarshan Seshadri—VP of AI, Data Science, and Foundations Engineering at Alto Pharmacy—joins us to explore what it takes to build high-stakes AI systems that people can actually trust. He shares lessons from deploying machine learning and LLMs in healthcare, where speed, safety, and uncertainty must be carefully balanced. We talk about designing A…

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Episode 17: The Incentive Problem in Shipping AI Products — and How to Change It 53:52

5M ago53:52

53:52

Roberto Medri, VP of Data Science at Instagram, explains why most experiments fail, how misaligned incentives warp product development, and what it takes to drive real impact with data science. He shares what teams get wrong about launches, why ego gets in the way of learning, and how Instagram turned Reels from a struggling product into a global s…

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Episode 16: How Human-Centered AI Actually Gets Built 47:22

6M ago47:22

47:22

Fei-Fei Li—co-director of Stanford’s Human-Centered AI Institute and one of the most respected voices in the field—reflects on AI’s evolution from the early days of ImageNet to the rise of foundation models. She explains why spatial intelligence may be the next major shift, how human-centered design applies in practice, and why AI should be underst…

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Episode 15: Why Good Metrics Still Lead to Bad Decisions — and How to Fix It 54:17

6M ago54:17

54:17

Eoin O'Mahony—data science partner at Lightspeed, former Uber science lead, and one of the early architects of the system that kept NYC’s Citi Bikes available across the city—argues that positive metrics are meaningless if you don’t understand the mechanism behind them. At Uber, he was careful to make sure his launches both looked good on paper and…

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Episode 14: Why Most Companies Aren’t Actually AI Ready (and What to Do About It) 51:58

7M ago51:58

51:58

Barr Moses—co-founder and CEO of Monte Carlo—thinks we’re headed for an AI reckoning. Companies are building fast, but most are still managing data like it’s 2015. In this episode, she shares high-stakes failure stories (like a $100M schema change), explains why full-stack observability is becoming essential, and breaks down how LLM agents are alre…

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Episode 13: The End of Programming As We Know It 1:23:09

7M ago1:23:09

1:23:09

Tim O’Reilly—founder of O’Reilly Media and one of the most influential voices in tech—argues we’re not witnessing the end of programming, but the beginning of something far bigger. He draws on past computing revolutions to explore how AI is reshaping what it means to build software, why real breakthroughs come from the edge—not incumbents—and what …

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Episode 12: Your Machine Learning Solves The Wrong Problem 54:40

8M ago54:40

54:40

Stefan Wager—Professor at Stanford and expert on causal machine learning—has worked with leading tech companies including Dropbox, Facebook, Google, and Uber. He challenges the widespread assumption that better predictions mean better decisions. Traditional machine learning excels at prediction, but is prediction really what your business needs? St…

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Episode 11: What Comes After Code? The Role of Engineers in an AI-Driven Future 1:05:44

8M ago1:05:44

1:05:44

Peter Wang—Chief AI Officer at Anaconda and a driving force behind PyData—challenges conventional thinking about AI’s role in software development. As AI reshapes engineering, are we moving beyond writing code to orchestrating intelligence? Peter explores why companies are fixated on models instead of integration, how AI is breaking traditional sof…

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Episode 10: AI Won't Save You But Data Intelligence Will 59:42

9M ago59:42

59:42

Ari Kaplan—Global Head of Evangelism at Databricks and a pioneer in sports analytics—explains why businesses fixated on AI often overlook the real advantage: making better decisions with their own data. He shares lessons from his work building analytics teams for Major League Baseball, advising McLaren’s F1 strategy, and helping companies apply AI …

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Episode 9: Why 90% of Data Science Fails—And How to Fix It -- With Eric Colson 1:09:40

9M ago1:09:40

1:09:40

In this episode of High Signal, Eric Colson—former Chief Algorithms Officer at Stitch Fix and VP of Data Science and Machine Learning at Netflix—breaks down why most companies fail to unlock the full potential of their data science teams. Drawing from years of experience leading data functions at top tech companies, Eric shares how organizations ca…

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Episode 8: From Zero to Scale: Lessons from Airbnb and Beyond 1:06:42

10M ago1:06:42

1:06:42

In this episode of High Signal, Elena Grewal—former Head of Data Science at Airbnb, political consultant, professor at Yale, and ice cream shop owner—shares her journey of building data teams that scale across vastly different contexts. Drawing on her experiences in tech, consulting, and brick-and-mortar, Elena offers practical lessons on leadershi…

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Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams 1:18:44

10M ago1:18:44

1:18:44

In this episode of High Signal, Chris Wiggins—Chief Data Scientist at The New York Times, Professor at Columbia University, and co-author of How Data Happened—shares how organizations can move beyond prediction to actionable decision systems. Drawing on his work at The New York Times and in academia, Chris explains how to scale data teams, optimize…

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Episode 6: What Happens to Data Science in the Age of AI? 1:18:23

11M ago1:18:23

1:18:23

In this episode of High Signal, Hilary Mason—renowned data scientist, entrepreneur, and co-founder of Hidden Door—shares her unique insights into the evolving world of data science and generative AI. Drawing from her pioneering work at Fast Forward Labs, Bitly, and Hidden Door, Hilary explores how creativity, judgment, and empathy are reshaping the…

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Episode 5: The Hard Truth About Building AI Systems and What Most Leaders Miss About AI 1:02:06

11M ago1:02:06

1:02:06

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 strategi…

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Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong 51:16

12M ago51:16

51:16

Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies. Ramesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the r…

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Episode 3: Data Science Meets Management: Teamwork, Experimentation, and Decision-Making 52:12

1y ago52:12

52:12

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 ma…

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Episode 2: Fooling Yourself Less: The Art of Statistical Thinking in AI 1:00:51

1y ago1:00:51

1:00:51

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 causa…

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Episode 1: The Next Evolution of AI: Markets, Uncertainty, and Engineering Intelligence at Scale 1:15:12

1y ago1:15:12

1:15:12

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 ca…