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 ...
E159 - Zero-Data AI, Agentic Systems & Next-Gen Video Models - Agrin Hilmkil
AIAW Podcast
2 hours 6 minutes
6 months ago
E159 - Zero-Data AI, Agentic Systems & Next-Gen Video Models - Agrin Hilmkil
Join us in this week’s episode of AIAW Podcast as we sit down with Agrin Hilmkil, Member of Technical Staff at Latent Labs, for a no-nonsense dive into the frontlines of AI innovation. From the latest LLM drops and agentic AI trends to training hacks and experimental breakthroughs, Agrin unpacks it all with clarity and insight. We also break down key takeaways from Google I/O, including AI-powered search, the Imagine 4 image generator, and Vue 3’s lip-synced video output—plus a bold look at s...
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 ...
