Cisco aims AI advancements at data center infrastructure

It wasn’t that long ago that ideas about revamping data-center networking operations to handle AI workloads would have been confined to a whiteboard. But conditions have changed drastically in the past year.

“AI and ML were on the radar, but the past 18 months or so have seen significant investment and development – especially around generative AI. What we expect in 2024 is more enterprise data-center organizations will use new tools and technologies to drive an AI infrastructure that will let them get more data, faster, and with better insights from the data sources,” said Kevin Wollenweber, senior vice president and general manager of Cisco’s networking, data center and provider connectivity organization. Enterprises also will be able to “better handle the workloads that entails,” he said.

A flurry of recent Cisco activity can attest to AI’s growth at the enterprise level.

Cisco’s $28 billion Splunk acquisition, which closed this week, is expected to drive AI advancements across Cisco’s security and observability portfolios, for example. And Cisco’s newly inked agreement with Nvidia will yield integrated software and networking hardware that promises to help customers more easily spin up infrastructure to support AI applications.

As part of the partnership, Nvidia’s newest Tensor Core GPUs will be available in Cisco’s M7 Unified Computing System (UCS) rack and blade servers, including UCS X-Series and UCS X-Series Direct, to support AI and data-intensive workloads in the data center and at the edge, the companies stated. The integrated package will include Nvidia AI Enterprise software, which features pretrained models and development tools for production-ready AI.

“The Nvidia alliance is actually an engineering partnership, and we are building solutions together with Nvidia to make it easier for our customers – enterprises and service providers – to consume AI technology,” Wollenweber said. The technologies they deliver will enable AI productivity and will include toolsets to build, monitor and troubleshoot the fabrics so they run as efficiently as possible, Wollenweber said. “Driving this technology into the enterprise is where this partnership will grow in the future.”