Data Radicals Podcast

Today, data intelligence software represents a $9B market. How did this term originate, and what part will it play in the age of AI? Learn why recognized analyst Stewart Bond coined the term and why he predicts the CDO will rival the CIO’s influence by 2028.

AI is reshaping the fabric of society. What will that mean? In this wide-ranging interview, Jeremy Kahn reveals the potential impact of AI on our jobs, warfare, and middle-class opportunities – and the role regulation might play.

AI is poised to transform financial services. Learn how the CDO of Singapore’s leading digital bank GXS is leveraging AI to create game-changing financial products and improve customer service, drawing on her experience as a climate scientist and access to alternative data sources.

In this unique episode, we introduce "Saul GP Talinsky," an AI iteration of Saul Alinsky, the pioneering force behind community organizing and the influential author of Rules for Radicals. The dialogue bridges the past and present, highlighting how modern data analytics culture echos Alinsky's ethos of empowerment and societal change. Through the lens of data, Alinsky's AI counterpart illustrates the transformative potential in both grassroots activism and corporate realms, advocating for a future where data-driven insights fuel innovation, challenge traditional paradigms and foster more just and equitable decision-making.

Edo Liberty, CEO and founder of Pinecone, introduces the impact of vector databases on AI, likening them to Esperanto for algorithms—a universally understandable language that transforms intricate data into an easily interpretable format for AI systems. Unlike traditional databases' clunky, one-size-fits-all approach, they make AI smarter, faster, and infinitely more useful. As the fabric of AI's cognitive processes, vector databases are the hidden engine behind the Generative AI revolution.

Sanjeevan Bala, ITV's Chief Data & AI Officer and DataIQ’s most influential person in data, embraces the ubiquity of data in the enterprise by embedding domain-specific data ‘squads’ within business units to localize decision-making. He discusses how, unlike monolithic data teams, meshy data organizations are the best way to align data initiatives with business value.

What does baseball have to do with data? Ari Kaplan, head of evangelism at Databricks, was instrumental in bringing a data-driven approach to a previously gut-driven sport and inspiring the Moneyball book and movie. Ari explains how businesses can learn from sports analytics, why a data culture is so critical to success, and how AI and generative AI are, literally, changing the game.

In a world of Neflix queues and doom-scrolling, Ars Technica’s Nate Anderson consults an unlikely source: Friedrich Nietzsche. The author of In Emergency, Break Glass: What Nietzsche Can Teach Us about Joyful Living in a Tech-Saturated World prescribes an “information diet” and adapts the German philosopher’s passionate quest for meaning into a world overwhelmed by “content.”

Guy Scriven, U.S. Technology Editor at The Economist, offers insights into the evolving landscape of AI adoption and implementation. He explains the cautious optimism surrounding AI applications — emphasizing the need for robust data governance — and shares his perspective on AI’s opportunities, challenges, and future trends.