MIT and Microsoft researchers develop Murakkab system to optimize AI agent workflow efficiency
By
Adam Zewe | MIT News
Summary
Researchers from MIT and Microsoft have developed "Murakkab," an automated system that streamlines the design and optimization of agentic AI workflows. Agentic workflows chain together multiple AI models and external tools to handle complex tasks, but their fragmented nature often leads to wasted computation, energy, and cost. Murakkab addresses these inefficiencies by intelligently optimizing how these workflows are designed and deployed, reducing computational overhead and energy consumption while improving overall efficiency for AI applications.
Source
bskyMIT and Microsoft researchers develop Murakkab system to optimize AI agent workflow efficiencynews.mit.eduKey quotes
· 3 pulledAgentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it.
But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy, and cost.
To improve efficiency, researchers from MIT and Microsoft developed an intelligent system that streamlines the process of designing agentic workflows and automatically optimizes how those workflows are implemented.
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