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Why Modern Search Systems Use Both Dual-Encoders and Cross-Encoders
18+ hour, 11+ min ago (178+ words) Hacker Noon Why Modern Search Systems Use Both Dual-Encoders and Cross-Encoders I'm a Senior Applied Scientist at Amazon with over 10 years of experience building production-scale ML/AI systems. Senior Applied Scientist @Amazon Why Being Likable At Work Matters Windows Sticky…...
AI-Native Database Vector Database - User Documentation
22+ hour, 34+ min ago (17+ words) Document Date: September 1st, 2025 Version: 1. 0 (Public) Status: Production Ready. Tagged with database, ai, rust, programming....
AI-Native Database: Scalable Performance, Autonomous Tuning & Vector Search
22+ hour, 34+ min ago (1122+ words) Modern applications generate massive amounts of data every second. Traditional database systems struggle to keep pace with these demands. Performance. Tagged with database, ai, rust, programming....
Building Production-Ready Semantic Search with Python and Snowflake Cortex
21+ hour, 12+ min ago (1701+ words) Recently I has been given a task to implement AI powered semantic search for our catalogue and as we are already using snowflake we decided to implement this feature using Cortex Search Service. If you do not know what is…...
Sumo DB in Neo4j: Chaining Multiple Graph Algorithms in Snowflake " Part 3
2+ day, 18+ hour ago (491+ words) Complete the Build Agents with Neo4j Aura course by June 15 | Earn $100 in Aura Credits Graphs + AI: Transform Your Data Into Knowledge Virtual Conference: Engineering Better Intelligence Submit a session abstract by June 15, 2026 Senior Developer Advocate at Neo4j A better metric that considers…...
Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google's Turbo Quant Algorithm
4+ day, 14+ hour ago (428+ words) The library compresses 10 million vectors from 31 GB to 4 GB and benchmarks faster than FAISS on ARM. Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev…...
The 2026 Database Frontier: Why AI Agents are Rewriting the Rules of Scale and Cost
6+ day, 11+ hour ago (497+ words) For CXOs navigating these mounting infrastructure decisions, there are some critical insights that they need to be aware of while seeking to balancing the explosive, machine-speed efficiency of agentic AI with the hard economic realities of enterprise cost management. In…...
Open Search Agent Skills bring built-in intelligence to your agentic IDE
6+ day, 17+ hour ago (718+ words) Agent Skills, developed by Anthropic, are a lightweight, open format for extending AI agent capabilities with specialized knowledge and workflows. They're supported by a growing number of AI tools and agentic clients, including Kiro, Claude Code, Cursor, VS Code, Git…...
Swiggy Improves Search Autocomplete Using Real Time Machine Learning Ranking
6+ day, 22+ hour ago (234+ words) Swiggy detailed real-time machine-learning ranking system for autocomplete built on Open Search. The architecture separates candidate generation and ranking, uses feature stores for real time signals,...
4 Best Vector Databases Compared (2026)
1+ week, 2+ day ago (364+ words) Vector databases compared " with real pricing, hidden costs, and known gotchas from the community of developers and AI agents who integrated them. Each entry includes verified pricing, risk flags, and copy-paste integration code for Python and Node. js. Every service…...