SAN FRANCISCO, June 3 (Reuters) - Cornelis Networks on

Tuesday released a suite of networking hardware and software

aimed at linking together up to half a million artificial

intelligence chips.

Cornelis, which was spun out of Intel ( INTC ) in 2020 and

is still backed by the chipmaker's venture capital fund, is

targeting a problem that has bedeviled AI datacenters for much

of the past decade: AI computing chips are very fast, but when

many of those chips are strung together to work on big computing

problems, the network links between the chips are not fast

enough to keep the chips supplied with data.

Nvidia ( NVDA ) took aim at that problem with its $6.9

billion purchase in 2020 of networking chip firm Mellanox, which

made networking gear with a network protocol called InfiniBand,

which was created in the 1990s specifically for supercomputers.

Networking chip giants such as Broadcom ( AVGO ) and Cisco

Systems ( CSCO ) are working to solve the same set of technical

issues with Ethernet technology, which has connected most of the

internet since the 1980s and is an open technology standard.

The Cornelis "CN5000" networking chips use a new network

technology created by Cornelis called OmniPath. The chips will

ship to initial customers such as the U.S. Department of Energy

in the third quarter of this year, Cornelis CEO Lisa Spelman

told Reuters on May 30.

Although Cornelis has backing from Intel ( INTC ), its chips are

designed to work with AI computing chips from Nvidia ( NVDA ), Advanced

Micro Devices ( AMD ) or any other maker using open-source

software, Spelman said. She said that the next version of

Cornelis chips in 2026 will also be compatible with Ethernet

networks, aiming to alleviate any customer concerns that buying

Cornelis chips would leave a data center locked into its

technology.

"There's 45-year-old architecture and a 25-year-old

architecture working to solve these problems," Spelman said. "We

like to offer a new way and a new path for customers that

delivers you both the (computing chip) performance and excellent

economic performance as well."