Microsoft's new vulnerability-scanning system, codenamed MDASH, scored 88.45% on the CyberGym benchmark, surpassing single-model systems from Anthropic and OpenAI by using more than 100 specialized AI ...
Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating ...
New custom-built agentic AI solution cuts the procurement cycle duration from 90 days to under 30 days, entirely behind ...
Microsoft researchers this week unveiled a new multi-agent AI system, aimed to help enterprises automate complex tasks typically requiring human intervention. Named Magnetic-One, the open source ...
Due to the lack of domain classification theory for domain-specific machine translation, the quality of translation in this area is low. We propose a domain classification system based on HNC and ...
What if you could design a system where multiple specialized agents work together seamlessly, each tackling a specific task with precision and efficiency? This isn’t just a futuristic vision—it’s the ...
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 ...
As artificial intelligence (AI) becomes more common in health care, from managing records to assisting with medication decisions, researchers at the Icahn School of Medicine at Mount Sinai are asking ...
The landscape of artificial intelligence is undergoing a significant transformation. As the capabilities of large language models grow, we are beginning to see a shift away from isolated ...
This paper focuses on the problem of active defense and achieving asymptotic consensus control in hybrid multi-agent systems under network attacks. Considering the influence of Byzantine nodes, on the ...
Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of sustained effort. Recent advances in large language models (LLMs) have ...
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Multi-agent adoption to rise 58% by 2027

MuleSoft said governance and integration remain key concerns as more AI agents are deployed across enterprises. Multi-agent adoption is expected to rise 58% by 2027 as organisations move toward ...