By Light Reading
Publication Date: 2026-08-25 09:29:00
“Reproducing kernel Hilbert space” (RKHS) is not a sequence of words that would be strung together in many conversations, even by someone immersed in technology at Nokia. It describes an algorithm used in machine learning, little known outside expert circles, and has been largely ignored by Nokia’s radio access network (RAN) people simply because the infrastructure couldn’t handle it. “We never used it because it’s very mathematically compute-intensive,” said Pallavi Mahajan, the Finnish company’s chief technology officer. “It has a lot of vector computation.”
That all changes now. “With GPUs, you can do that, and you get efficiency,” said Mahajan. Those GPUs are the graphics processing units designed and sold by Nvidia, the world’s biggest company by market capitalization. They have underpinned the generative AI boom, providing a much more powerful platform than older central processing units (CPUs) to train large language models (LLMs). Nokia’s experts believe they could be equally valuable in the RAN as the industry begins work on 6G.
Around ten months have now elapsed since Nokia accepted a $1 billion investment from Nvidia. That came with a sector-shaking announcement of plans to design RAN software based on CUDA, the chipmaker’s platform, and make GPUs integral to Nokia’s future 5G and 6G products. For a time, these will coexist with the custom silicon that Nokia obtains from Marvell Technology, its longstanding 5G partner. But Nokia has been emphatic: the Marvell…
