Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
Agent skills shift AI agents toward procedural tasks with skill.md steps; progressive disclosure reduces context window bloat in real use.
Databricks and Tonic.ai have partnered to simplify the process of connecting enterprise unstructured data to AI systems to reap the benefits of RAG. Learn how in this step-by-step technical how-to.
While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as muc ...
Gigasoft releases ProEssentials v10 with GPU compute shaders and publishes six-part WPF chart library comparison for ...
XDA Developers on MSN
This self-hosted tool makes my local LLMs feel exactly like ChatGPT, but nothing leaves my network
It's perfect for privacy-conscious folks looking to break away from ChatGPT ...
Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower ...
The open source MySQL spin-off has steadily added features all its own. Here are five good reasons to switch to MariaDB.
Are AGENTS.md files actually helping your AI coding agents, or are they making them stupider? We dive into new research from ETH Zurich, real-world experiments, and security risks to find the truth ...
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