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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 awareness and low-latency decision-making, and why they’re central to the future of scalable, ethical, and sovereign AI systems. Tune in for a deep dive into the systems powering tomorrow’s most advanced AI applications.
Follow us on youtube: https://www.youtube.com/@aiawpodcast
By HyperightIn 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 awareness and low-latency decision-making, and why they’re central to the future of scalable, ethical, and sovereign AI systems. Tune in for a deep dive into the systems powering tomorrow’s most advanced AI applications.
Follow us on youtube: https://www.youtube.com/@aiawpodcast

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