How DeepSeek changes the gen AI equation for CIOs

“DeepSeek’s R1 model thus represents a pivotal shift, suggesting that the future of gen AI lies in innovative, cost-efficient approaches rather than the traditional paradigm of scaling through sheer computational force,” Gartner researchers, including Haritha Khandabattu, Jeremy D’Hoinne, Rita Sallam, Leinar Ramos, and Arun Chandrasekaran, wrote in a research note Wednesday.

Peter Rutten, research VP for performance intensive computing and worldwide infrastructure research at IDC, says the key takeaway from DeepSeek’s results is that the current approach to AI training — which is based on the theory that AI can only improve with bigger, more, and faster architecture — is not justified.

“New approaches to algorithm, framework, and software for AI development deliver comparable or even better results than, for example, the latest version of ChatGPT, with the same accuracy and at a fraction of the infrastructure cost,” says Rutten. “What this means is that AI training doesn’t need to be the sole domain of hyperscalers who can afford to invest billions of dollars into large infrastructure buildouts.”

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