⚠️ IMPORTANT NOTE ON THE DATA: This video is based on deep-dive research into Google Engineering papers, patents, and recent AI conference presentations (NeurIPS). While I am presenting the dates (like Jan 14th and Jan 23rd) and names (like VideoPrism) based on the latest available technical logs and research papers, Consider this a "Forecast" of the backend mechanics that are currently shaping the platform. I’ve linked the actual research papers below so you can see the math for yourself. 📚 THE EVIDENCE LOCKER (Sources & Research) For those who want to see the code and the papers mentioned in the video: The "GIST" Update (Redundancy Filter): Concept: Greedy Independent Set Thresholding (Reducing duplicate content). Paper: GIST: Greedy Independent Set Thresholding (NeurIPS) - https://openreview.net/forum?id=5aeD5UbiLv Google Research Blog: Introducing GIST - https://research.google/blog/introducing-gist-the-next-stage-in-smart-sampling/ The "Semantic ID" System (The new "Tags"): Concept: Replacing random IDs with "Meaningful" Tokens. Research: PLUM: Adapting Language Models for Recommendation - https://www.shaped.ai/blog/youtube-semantic-ids-ctr-lift Example Entity: Elon Musk Knowledge Graph ID: /m/03_d0 The "Information Gain" Score: Patent: Contextual Estimation of Link Information Gain - https://patents.google.com/patent/US20200349181A1/en Gemini "Personal Intelligence" Update (Jan 2026): Update: Gemini 3 / Cross-Platform Integration - https://blog.google/products-and-platforms/products/gemini/gemini-3-gemini-app/
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