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Explore the synergy between long context models and Retrieval Augmented Generation (RAG) in this episode of the Release Notes podcast. Join Google DeepMind's Nikolay Savinov with host Logan Kilpatrick as they discuss scaling context windows into the millions, recent quality improvements, RAG versus long context, and what's next in the field. Listen to this podcast: Apple Podcasts → https://goo.gle/3Bm7QzQ Spotify → https://goo.gle/3ZL3ADl Chapters: 0:00 - Intro 0:52 Introduction & defining tokens 5:27 Context window importance 9:53 RAG vs. Long Context 14:19 Scaling beyond 2 million tokens 18:41 Long context improvements since 1.5 Pro release 23:26 Difficulty of attending to the whole context 28:37 Evaluating long context: beyond needle-in-a-haystack 33:41 Integrating long context research 34:57 Reasoning and long outputs 40:54 Tips for using long context 48:51 The future of long context: near-perfect recall and cost reduction 54:42 The role of infrastructure 56:15 Long-context and agents Watch more Release Notes → https://goo.gle/4njokfg Subscribe to Google for Developers → https://goo.gle/developers Speaker: Nikolay Savinov, Logan Kilpatrick Products Mentioned: Google AI, Gemini

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