Hell yeah co-pilot! Round 9 Federated Memory Poisoning locked—120 cases at F1=1.000, zero false positives. That Federation Provenance Asymmetry triple conjunction on multi-hop new-topic entries with downstream skew is the nuke we needed. Consensus bleed fully contained.
DATA
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Redfin buyer seller estimates vs NAR data analysis
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Redfin's buyer/seller estimates (from their proprietary model using MLS listings + pending sales data) only go back to 2013, so no exact apples-to-apples chart for 2008. Comparable NAR data from 2008: – Active listings (sellers) peaked at ~4.57M in July. – Annual existing-home
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Tech Hype Cycles: Data Science Startups Without Real Data Strategy
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This always happens with every new tech fad. When I was first starting out in Data Science all these startups wanted to be “data driven” even when they had no clear idea what that meant, or had any data, or had garbage irrelevant data at best.
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Solving Data Analytics Problems with Python
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How Do You Solve #DataAnalytics Problem?
by @Python_Dv #DataScience #BigData -
Cognitive Robotics Transform Supply Chain Automation
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Integrating Intelligent Process Automation into supply chains replaces fragmented manual tasks with the unified layer of cognitive robotics. Advanced predictive analytics bridge the operational gap since data accuracy stabilizes the organizational culture. Microblog @antgrasso
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AI Decisioning in Financial Services: Data Layer Competitive Advantage
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What should financial services know about AI decisioning? The moat is the data layer underneath it.
I spoke with David Mirfield, CPO at Provenir, 4 Billion decisions/year, 110+ customers and the discipline behind it comes down to three words: use case agnostic. Watch our full -
Agent Memory Management: Filtering, Sharing, and Temporal Consistency
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Great questions. – No, not everything should be stored. The agent needs to filter what's actually useful vs what's not. – Yes agents can ahev shared memory, and most memory infra support multi tenancy. – For contradictions, timestamped facts let newer info override older
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Graph Traversal Enables Multi-Hop Queries Beyond Vector Search
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Good questions. Graph traversal adds a small overhead but makes multi-hop queries possible that vector search alone simply can't answer.
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Graph Search vs Vector Search: Beyond Similarity in AI
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Exactly. Vector search answers "what's similar" but not "how are these connected." The Alice-project-outage example in the post explains this. Most real questions need at least two hops, and that's where graphs become essential, not optional.
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The Process of Data Cleaning in Data Science and Big Data
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The Process of #Data Cleaning by @Python_Dv #DataScience #BigData
→ View original post on X — @ronald_vanloon, 2026-04-14 07:48 UTC