The industry hype says "more agents is all you need," but new data shows that strictly sequential tasks and tool-heavy ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

AI agents are no longer limited to research projects. They now operate in real-world systems where they manage automation, ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

Enterprises are likely to shift from single-task AI to multi-agent systems, enabling autonomous, adaptive operations, but trust and orchestration remain problematic.

For many enterprises, there continue to be barriers to fully adopting and benefiting from agentic AI. IBM is betting the blocker isn't building AI agents but governing them in production. At its ...

Tech industry visionaries foresee a fundamental shift in network intelligence. Microsoft CEO Satya Nadella envisions humans collaborating with AI agent swarms, while Nvidia CEO Jensen Huang projects a ...

The researchers found single AI agents do better at sequential tasks, multi-agent workflows at ones that can be done in ...

When I first started working with multi-agent collaboration (MAC) systems, they felt like something out of science fiction. It’s a group of autonomous digital entities that negotiate, share context, ...

Cisco's Agntcy project is the latest AI framework to find refuge at the Linux Foundation.… Developed by Cisco in collaboration with LangChain and Galileo, the Agntcy project bills itself as the ...

AI has already made significant strides in modern enterprises. According to McKinsey researchers, "92% of companies plan to increase their AI investments," and this trend is expected to grow. From ...