🔍 RAG - tyler · Scour

How I Built a Real-Time AI Stock Advisor Using Elasticsearch, MCP, and LLMs 📡RSS

hackernoon.com·8h

Open source memory layer so any AI agent can do what Claude.ai and ChatGPT do 🧠AI

alash3al.github.io·6d·Hacker News

Designing a Memory System for LLM-Based Agents 💬Prompt Engineering

zby.github.io·6d·Hacker News

Quantitative Analysis of Hallucination Bias in LLM Counting Tasks and Suppression Effects via Structured Protocol (KIS) 💬Prompt Engineering

zenodo.org·4d·Hacker News

Reimagining Kernel Generation at the PTX Layer: An LLM System Learning from DSLs to Outperform Them 🔧Code Generation

standardkernel.com·3d·Hacker News

Can agents replace the search stack? 📈Query Optimization

softwaredoug.com

·3d·Hacker News

Language Anchoring: A Systematic Method for LLM Multilingual Adaptation 🧠AI

github.com·4d·Hacker News

Your Embedding Model Will Deprecate. Here's What to Do. 🗂️Vector Databases

hackernoon.com·18h

nambok/mentedb: A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre assembly. Not a wrapper, a ground up storage engine that thinks. ⚙️Systems Programming

github.com·6d·Hacker News

More Memory Won’t Fix Your AI Agents 🤖Agent-Based Simulations

hackernoon.com·6h

Guess-Verify-Refine: Data-Aware Top-K for Sparse-Attention Decoding on Blackwell via Temporal Correlation 🌸Bloom Filters

arxiv.org·3d·Hacker News

Building a High-Scale Real-Time Recommendation Engine with Feature Stores and Redis Observability 🗂️Vector Databases

hackernoon.com·3d

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