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AIAW Podcast
Hyperight
184 episodes
6 days ago
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 ...
Show more...
Technology
Business
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E161 - Responsible Use of AI - Luis Martinez
AIAW Podcast
2 hours 18 minutes
2 months ago
E161 - Responsible Use of AI - Luis Martinez
In this episode, we’re joined by Luis Martínez, AI Compliance Expert at Assa Abloy, for a thought-provoking conversation on one of the most urgent topics in the field: the responsible use of AI. With a background in telecommunications and regulatory affairs, Luis brings a unique perspective to the challenges of building trustworthy AI systems inside complex, global organizations. We explore what it actually means to be AI compliant in practice, how harmonized standards and certification...
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 ...