in ai, memory is a moat with social, relevant network size correlated with value for the user (network is a moat). with ai, every relevant memory extracted from user interactions increases the product value for the user. true or false?
DATA
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Databricks AI Governance Framework for Enterprise Programs
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Our new Databricks AI Governance Framework is your comprehensive guide to implementing enterprise AI programs responsibly and effectively. The framework provides a structured approach to AI development, spanning 5 foundational pillars for building a responsible and resilient AI
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Bad dataset quality impacts AI model performance outcomes
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The dataset I gave the AI was bad, it worked with that data.
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ChatGPT Agent Limitations: Data Analysis Power and Human AI Collaboration
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An example of the power & limitations of ChatGPT agent I asked it to analyze a dataset from Kaggle, and turn it into a PPT and Excel. It made no errors, but I thought some of the data was odd. I gave that feedback & the AI figured out the data was bad and why. Human + AI needed
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McLaren Accelerates Data Insights with AI Technology
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Proud to help McLaren unlock faster data insights and speed to market
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AI Reshaping Finance: Data Analysis to Decision-Making
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Exciting to see AI reshaping finance from data analysis to decision-making
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Vibe Scraping: Emerging Data Extraction Concept in AI
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I think I'm going to call this "vibe scraping"
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Closing the 100,000 Year Data Gap in Robotics
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Looking fwd to presenting this talk @Google next Thurs at noon. It will be live in person in Mountain View CA (not online) but is free and open to the public: How to Close the 100,000 Year “Data Gap” in Robotics
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Gemini’s Tokenization of YouTube Videos for Large Recommender Models
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criminally underrated talk from @devanshtandon_ Gemini powers YouTube's Large Recommender Model by **tokenizing every video on youtube** (SemanticID) – a vocabulary several OoMs larger than English, CONTINUOUSLY PRETRAINED every day. can reason across titles/descriptions, throws
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SLMs and Mini-Agents Power Reliable Agentic AI Workflows
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At #DataAISummit, @LaminiAI CEO @realSharonZhou explored how SLMs and mini-agents can power reliable agentic workflows. Learn about memory RAG, MoME-based memory tuning, and real-world use cases like text-to-SQL and code analysis: https://
databricks.com/dataaisummit/s
ession/composing-high-accuracy-ai-systems-slms-and-mini-agents?utm_source=twitter&utm_medium=organic-social&utm_scid=701vp00000d7qrxia3
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