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 ...
E160 - AI Summer 2025 Recap: GPT-5, ChatGPT Agent & More
AIAW Podcast
2 hours 25 minutes
3 months ago
E160 - AI Summer 2025 Recap: GPT-5, ChatGPT Agent & More
Is OpenAI preparing to monetize with ads? Was the latest GPT-5 release a strategic decision or a true technical leap? In this Pre-Season 11 Summer Special of the AIAW Podcast, Anders Arpteg and Henrik Göthberg are joined by Jesper Fredriksson (AI Engineer Lead, Volvo Cars) and Robert Luciani (AI Wizard, Negatonic AB) to unpack the biggest AI news from June–August 2025. We dive into GPT-5’s benchmark and coding performance, the hunt for better AI metrics, Perplexity’s bid on Google Chrome, Met...
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 ...
