In Episode 170 of the AIAW Podcast, we’re joined by Jim Dowling, CEO of Hopsworks, co-creator of featurestore.org, and author of the upcoming O’Reilly book Building Machine Learning Systems with a Feature Store. Known as "Mr. Feature Store," Jim walks us through the evolution of AI infrastructure. From traditional batch learning to real-time, agentic workflows powered by vector databases, RAG, and LLMs. We discuss how feature stores serve as the memory layer of AI agents, enabling contextual ...
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In Episode 170 of the AIAW Podcast, we’re joined by Jim Dowling, CEO of Hopsworks, co-creator of featurestore.org, and author of the upcoming O’Reilly book Building Machine Learning Systems with a Feature Store. Known as "Mr. Feature Store," Jim walks us through the evolution of AI infrastructure. From traditional batch learning to real-time, agentic workflows powered by vector databases, RAG, and LLMs. We discuss how feature stores serve as the memory layer of AI agents, enabling contextual ...
E154 - King´s AI Enablement Toolbox - Carl Carlheim-Gyllensköld & Patrick Juhl
AIAW Podcast
2 hours 37 minutes
7 months ago
E154 - King´s AI Enablement Toolbox - Carl Carlheim-Gyllensköld & Patrick Juhl
Join us for Episode 154 of the AIAW Podcast as we explore the transformative power of the AI Enablement Toolbox with Carl Carlheim Gyllensköld, AI Enablement Manager, and Patrick Juhl, AI Program Director at King. In this insightful conversation, our guests break down King's innovative approach—from a human-centric focus and hands-on workshops to pilot projects and the empowering role of CAKE Champions—that has revolutionized how teams adopt AI tools and drive productivity. Discover how these...
AIAW Podcast
In Episode 170 of the AIAW Podcast, we’re joined by Jim Dowling, CEO of Hopsworks, co-creator of featurestore.org, and author of the upcoming O’Reilly book Building Machine Learning Systems with a Feature Store. Known as "Mr. Feature Store," Jim walks us through the evolution of AI infrastructure. From traditional batch learning to real-time, agentic workflows powered by vector databases, RAG, and LLMs. We discuss how feature stores serve as the memory layer of AI agents, enabling contextual ...
