Microsoft's new vulnerability-scanning system, codenamed MDASH, scored 88.45% on the CyberGym benchmark, surpassing ...
The bottleneck in agentic computing isn’t a lack of orchestration; it is the orchestration itself. Building multi-agent ...
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% and speeding inference 2.4x.
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 ...
That would put Anthropic in a more direct fight with OpenAI and Microsoft — not just over model quality, but over the operating layer of AI agents.
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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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