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 ...
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 ...
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 ...
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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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