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 ...
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 ...
UIUC and Stanford's RecursiveMAS lets AI agents collaborate in embedding space instead of text, cutting token usage by 75% ...
How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...
Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As the CTO of an AI-native email management startup, I've spent the past year building multi ...
We just can’t seem to help ourselves. Our current infatuation with multi-agent systems risks mistaking a useful pattern for an inevitable future, just as we once did with microservices. Remember those ...
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Microsoft’s multi-agent AI system tops Anthropic’s Mythos on cybersecurity benchmark
Mythos has been MDASH’d. A new AI-powered system from Microsoft surpassed a headline-grabbing rival from Anthropic on a leading cybersecurity benchmark, using more than 100 specialized AI agents ...
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