Target Multiplai 2026 will spotlight multi-agent AI, bringing industry and academia together to discuss enterprise deployment ...

Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating ...

As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...

Many enterprises are moving from experimenting with single AI agents to a multi-level approach that spans functions such as ...

Multi-agent AI agent personality shapes outcomes in collaborative and negotiation workflows but not in structured coding, ...

Agentic AI moves beyond chatbots into systems that plan, use tools, and act. Learn key terms, architectures, risks, ...

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 ...

AI coding agents from OpenAI, Anthropic, and Google can now work on software projects for hours at a time, writing complete apps, running tests, and fixing bugs with human supervision. But these tools ...

Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company’s ...

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 ...

Zapier reports that AI agent evaluation is crucial for ensuring reliable performance in real-world scenarios, identifying ...