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 ...
All content for AIAW Podcast is the property of Hyperight and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
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 ...
E169– Homo Roboticus: Behind the Scenes with Alexander Norén
AIAW Podcast
2 hours 14 minutes
1 week ago
E169– Homo Roboticus: Behind the Scenes with Alexander Norén
In Episode 169 of the AIAW Podcast, we’re joined by Alexander Norén, journalist and economics correspondent at SVT, for a behind-the-scenes conversation on Homo Roboticus—the newly released second season of SVT’s acclaimed documentary series that began with Generation AI. While the series dives into how artificial intelligence is transforming work and society, this episode goes further, tackling the political and economic implications of automation that are often left out of mainstream ...
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 ...
