Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower cost than frontier models.

Agent skills shift AI agents toward procedural tasks with skill.md steps; progressive disclosure reduces context window bloat in real use.

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

SQL Server backups cannot be restored to older versions directly. Use Export and Import Data-Tier Application for cross-version database migration. Reconfigure permissions, logins, and connection ...

In this tutorial, we build an advanced, end-to-end learning pipeline around Atomic-Agents by wiring together typed agent interfaces, structured prompting, and a compact retrieval layer that grounds ...

agent-farm/ ├── src/agent_farm/ # Main Python package │ ├── main.py # Entry point, MCP server initialization │ ├── spec_engine.py # Spec Engine class (central component) │ ├── orgs.py # Organization ...

Abstract: The growing demand for high-bandwidth, zero-trouble services is imposing unprecedented challenges on optical communication networks. Traditional human-centric network management approaches ...

Một hệ thống tri thức toàn diện từ ingestion → storage → retrieval → agentic question answering, sử dụng SurrealDB native vector storage (HNSW), knowledge graph, và LangGraph orchestration.

A new technique developed by researchers at Shanghai Jiao Tong University and other institutions enables large language model agents to learn new skills without the need for expensive fine-tuning. The ...

Enterprise-ready foundation integrates with AWS agentic AI services through a Coveo-hosted MCP Server, helping ensure every agentic response is factual, contextual, and compliant MONTREAL, Dec. 1, ...

What if you could build an AI agent that not only automates your daily tasks but also adapts to your unique needs, seamlessly integrating with your favorite tools, analyzing vast datasets, and even ...

A team of AI researchers at Bloomberg have developed PExA, an agentic framework that achieved 70.2% execution accuracy, sharing one of the top positions on the Spider 2.0 (Snow) leaderboard, one of ...