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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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E157 - Human-Centered AI - Paulina Modlitba
AIAW Podcast
2 hours 3 minutes
6 months ago
E157 - Human-Centered AI - Paulina Modlitba
Get ready for a powerful conversation with Paulina Modlitba — MIT Media Lab alum, tech humanist, author, and public speaker with over 15 years in digital innovation and future-facing strategy. In this episode, Paulina will share how her early fascination with technology led her to explore the intersection of AI, creativity, and human values. She will unpack insights from Sweden’s evolving AI landscape, reveal why most AI projects still fail, and explain how ethics, clarity, and optimism can g...
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 ...