Microsoft Intros Open Source Multi-Agent AI System
        
        
        
        Microsoft researchers have unveiled a new open source multi-agent AI  system, aimed to help enterprises automate complex tasks typically requiring  human intervention.
Named Magnetic-One, the project is designed to handle a wide range of complex,  open-ended tasks on the web and in file-based environments. Microsoft said the  new system will allow AI agents to not only converse with users, but also execute  complex multi-step tasks — a leap for AI evolution, according to the company.
"It's the  difference between generative AI recommending dinner options to agentic  assistants that can autonomously place your order and arrange delivery,"  wrote Microsoft researchers. "It's  the shift from summarizing research papers to actively searching for and  organizing relevant studies in a comprehensive literature review."
Similar to Salesforce's Agentforce, Magnetic-One uses a  multi-agent system to automate and execute tasks. At the center of the system  is an "Orchestrator" agent that manages and coordinates four  specialized agents:  WebSurfer,  FileSurfer, Coder, and ComputerTerminal. Each agent is responsible for a  specific function, including web navigation, file handling, coding, and  command-line operations. The Orchestrator dynamically assigns subtasks,  monitors progress, and adapts its strategy as needed to complete complex tasks  with minimal human input.
    
 
  
 
 [Click on image for larger view.] Figure 1. Magnetic-One's multi-agent model.
"The Orchestrator plans, tracks progress, and re-plans to  recover from errors, while directing specialized agents to perform tasks like  operating a web browser, navigating local files, or writing and executing  Python code," wrote researchers with Microsoft AI. 
Microsoft is initially releasing Magnetic-One as an open source  project for researchers and developers. Although the system demonstrates strong  generalist capabilities, it remains below human-level performance and may still  encounter errors. As agentic systems become more capable, risks such as  unintended actions or potential misuse could increase, said Microsoft. 
Recognizing that agentic AI is still in its early stages, Microsoft  is counting on the public to help address these challenges and ensure that  future systems are both effective and secure through usage. To support this, the company is also introducing AutoGenBench, an evaluation tool designed to  rigorously test agentic tasks with built-in controls to minimize unwanted side  effects through repetition and isolation.
"AutoGenBench facilitates agentic evaluation and allows  adding new benchmarks. Using AutoGenBench, we can evaluate Magnetic-One on a  variety of benchmarks," wrote Microsoft. "Our criterion for selecting  benchmarks is that they should involve complex multi-step tasks, with at least  some steps requiring planning and tool use, including using web browsers to act  on real or simulated webpages. We consider three benchmarks in this work that  satisfy this criterion: GAIA, AssistantBench, and WebArena."
 Magnetic-One is available for download here.