knowledge management
30 articles about knowledge management in AI news
Andrej Karpathy's Personal Knowledge Management System Uses LLM Embeddings Without RAG for 400K-Word Research Base
AI researcher Andrej Karpathy has developed a personal knowledge management system that processes 400,000 words of research notes using LLM embeddings rather than traditional RAG architecture. The system enables semantic search, summarization, and content generation directly from his Obsidian vault.
New Research Proposes FilterRAG and ML-FilterRAG to Defend Against Knowledge Poisoning Attacks in RAG Systems
Researchers propose two novel defense methods, FilterRAG and ML-FilterRAG, to mitigate 'PoisonedRAG' attacks where adversaries inject malicious texts into a knowledge source to manipulate an LLM's output. The defenses identify and filter adversarial content, maintaining performance close to clean RAG systems.
Microsoft's Satya Nadella Details Internal 'Lean for Knowledge Work' AI Initiative
Microsoft CEO Satya Nadella described the company's internal application of AI to streamline knowledge work, framing it as a 'Lean' manufacturing-style efficiency push for cognitive tasks. The initiative focuses on using AI to reduce process friction and improve productivity across internal operations.
Knowledge-RAG v3.0: The Local RAG MCP Server That Finally Just Works
Knowledge-RAG v3.0 eliminates Docker/Ollama setup, adds hybrid search with cross-encoder reranking, and auto-indexes your docs—making private RAG in Claude Code a one-command install.
Stanford/CMU Study: AI Agent Benchmarks Focus on 7.6% of Jobs, Ignoring Management, Legal, and Interpersonal Work
Researchers analyzed 43 AI benchmarks against 72,000+ real job tasks and found they overwhelmingly test programming/math skills, which represent only 7.6% of actual economic work. Management, legal, and interpersonal tasks—which dominate the labor market—are almost entirely absent from evaluation.
New Research Diagnoses LLMs' Struggle with Multiple Knowledge Updates in Context
A new arXiv paper reveals a persistent bias in LLMs when facts are updated multiple times within a long context. Models increasingly favor the earliest version, failing to track the latest state—a critical flaw for dynamic knowledge tasks.
Understanding the Interplay between LLMs' Utilisation of Parametric and Contextual Knowledge: A keynote at ECIR 2025
A keynote at ECIR 2025 will present research on how Large Language Models (LLMs) balance their internal, parametric knowledge with external, contextual information. This is critical for deploying reliable AI in knowledge-intensive tasks where models must correctly use provided context, not just their training data.
Reinforcement Learning Ushers in New Era of Autonomous Knowledge Agents
Researchers are developing knowledge agents powered by reinforcement learning that can autonomously gather, process, and apply information. These systems represent a significant evolution beyond traditional language models toward more independent problem-solving capabilities.
Future-Proof Your AI Search: Why Static Knowledge Bases Fail Luxury Retail
New research reveals AI retrieval benchmarks degrade over time as information changes. For luxury brands using AI for product recommendations and clienteling, this means static knowledge bases become stale, hurting customer experience and sales.
VMLOPS's 'Basics' Repository Hits 98k Stars as AI Engineers Seek Foundational Systems Knowledge
A viral GitHub repository aggregating foundational resources for distributed systems, latency, and security has reached 98,000 stars. It addresses a widespread gap in formal AI and ML engineering education, where critical production skills are often learned reactively during outages.
UiPath Launches AI Agents for Retail Pricing, Promotions, and Stock Management
UiPath has announced new AI agents designed to autonomously handle core retail operations: dynamic pricing, promotional planning, and inventory gap resolution. This represents a significant move by a major automation player into agentic AI for retail.
Vendasta Launches 'CRM AI' for Automated Client Management
Vendasta has launched a new AI-powered CRM designed to autonomously update client records and manage tasks, aiming to close the 'execution gap' for businesses. This represents a shift towards proactive, agentic systems in business software.
The File Paradigm: How Simple File Systems Could Revolutionize AI Context Management
New research proposes treating all AI context as files within a unified system, potentially solving memory and organization challenges in complex AI workflows. This approach could dramatically simplify how AI systems access and manage information.
AI Learns from Its Own Failures: New Framework Revolutionizes Autonomous Cloud Management
Researchers have developed AOI, a multi-agent AI system that transforms failed operational trajectories into training data for autonomous cloud diagnosis. The framework addresses key enterprise deployment challenges while achieving state-of-the-art performance on industry benchmarks.
The Unix Philosophy Returns: How File Systems Could Solve AI's Memory Crisis
A new research paper proposes treating AI context management like a Unix file system, with OpenClaw demonstrating that storing memory, tools, and knowledge as files creates traceable, auditable AI systems. This approach could solve fragmentation and transparency issues plaguing current agent frameworks.
Anthropic's Claude Skills Implements 3-Layer Context Architecture to Manage Hundreds of Skills
Anthropic's Claude Skills framework employs a three-layer context management system that loads only skill metadata by default, enabling support for hundreds of specialized skills without exceeding context window limits.
How to Run Claude Code 24/7 Without Burning Your Context Window
Implement a hard 50K token session cap and a three-tier memory system (daily notes, MEMORY.md, PARA knowledge graph) to prevent context bloat and memory decay in long-running Claude Code agents.
How This Obsidian Vault Template Gives Claude Code a Long-Term Memory
A GitHub template creates a persistent knowledge graph for Claude Code, eliminating session amnesia and compounding engineering decisions across conversations.
Edge Computing in Retail 2026: Examples, Benefits, and a Guide
Shopify outlines the strategic shift toward edge computing in retail, detailing its benefits—real-time personalization, inventory management, and enhanced in-store experiences—and providing a practical implementation guide for 2026.
xAI Hires Wall Street Bankers and Credit Lenders to Train Grok on High-Level Finance
Elon Musk's xAI is recruiting finance professionals from Wall Street and credit lending institutions to train its Grok AI model on specialized financial knowledge. This move signals a targeted push to build domain expertise beyond general-purpose LLM capabilities.
Deloitte on Driving Adoption of the 'Human with Agentic AI' Era
Deloitte outlines the shift to a 'human with agentic AI' paradigm, where autonomous AI agents act as proactive partners. This requires new organizational strategies to integrate agents that can preserve institutional knowledge and interface with legacy systems.
How Claude-Code-Workflow Orchestrates Multiple CLI Agents for Complex Tasks
Install this CLI tool to coordinate multiple Claude Code agents for complex projects using semantic commands and session management.
How Non-Developers Can Use `claude --resume` and CLAUDE.md to Save Hours
Stop losing your work and repeating yourself. Use `claude --resume` to recover sessions and CLAUDE.md as a permanent knowledge base for any project.
Build Self-Evolving Skills for Claude Code: The GitHub Pattern That Grows Smarter With Use
A new GitHub pattern shows how to create Claude Code Skills that learn from each session, preventing knowledge loss and reducing repetitive context.
B2B and B2C Companies Increase AI Investment as Agentic Commerce Gains Traction
A new report highlights a significant uptick in AI investment across both B2B and B2C commerce sectors, driven by the emerging trend of 'agentic commerce'—where autonomous AI agents handle complex customer journeys. This signals a strategic shift from basic automation to intelligent, end-to-end task management.
Google's Groundsource: Using AI to Mine Historical Disaster Data from Global News
Google AI Research has unveiled Groundsource, a novel methodology using the Gemini model to transform unstructured global news reports into structured historical datasets. The system addresses critical data gaps in disaster management, starting with 2.6 million urban flash flood events.
New Research Proposes 'Level-2 Inverse Games' to Infer Agents' Conflicting Beliefs About Each Other
MIT researchers propose a 'level-2' inverse game theory framework to infer what each agent believes about other agents' objectives, addressing limitations of current methods that assume perfect knowledge. This has implications for modeling complex multi-agent interactions.
PSAD: A New Framework for Efficient Personalized Reranking in Recommender Systems
Researchers propose PSAD, a novel reranking framework using semi-autoregressive generation and online knowledge distillation to balance ranking quality with low-latency inference. It addresses key deployment challenges for generative reranking models in production systems.
CTRL-RAG: The AI Breakthrough That Could Eliminate Hallucinations in Luxury Client Service
New reinforcement learning technique trains AI to provide perfectly accurate, evidence-based responses by contrasting answers with and without supporting documents. This eliminates hallucinations in customer service, product recommendations, and internal knowledge systems.
TraderBench Exposes AI Trading Agents' Critical Weakness: They Can't Adapt to Real Markets
A new benchmark called TraderBench reveals that current AI trading agents fail to adapt to adversarial market conditions, scoring similarly across manipulated and normal scenarios. The research shows extended thinking helps with knowledge tasks but provides zero benefit for actual trading performance.