AIStor

In the previous blog of this series, we discussed the basic user-level functions of the Model Context Protocol (MCP) server for MinIO AIStor. We learned how to review a bucket’s contents, analyze objects, and tag them for future processing using human-language commands and simply chatting with the cluster via an LLM such as Anthropic Claude. In this blog, we’

GenAI is entering the agentic phase, with software agents collaborating with humans and other agents to reason and achieve complex goals. Agents are already demonstrating incredible intelligence and are very helpful with question answering, but as with humans, they need the ability to discover and access software applications and other services to actually perform useful work. The creators of such

Tl;dr: We train a small LLM to become good at reasoning with reinforcement learning (similar to the process that led to Deepseek R1) all against AIStor AIHub, an on-premises model repository. Based on the great GRPO demo by will brown. Motivation: A growing requirement for teams is the need for an organized, secure, "single source of truth"

Almost a year ago (actually 11 months ago), I wrote about the “Starving GPU Problem” and how the horsepower of Nvidia’s Graphic Processing Units (GPUs) could be so powerful that your network and your storage solution may not be able to keep up - preventing your expensive GPUs from being fully utilized. Well, in those short 11 months, a