Apple building M8 AI servers, talks with Nvidia, reports The Information

Investing.com -- Apple is developing an enterprise AI server built around its own M8 Ultra chips, with a target launch of 2029, and has held talks with Nvidia about using the chipmaker’s NVLink Fusion interconnect platform to link those chips together, The Information reported Wednesday.

Nvidia (NASDAQ: NVDA), which dominates the AI server market and earns roughly a fifth of its data-centre revenue from networking gear, is the most direct equity expression of that development: any Apple deal to adopt NVLink Fusion would add a new, large-volume customer while simultaneously confirming Nvidia’s strategy of monetising interconnect technology even as rival chips challenge its GPU franchise.

The planned server would come in two configurations — one pairing two M8 Ultra chips and one pairing four — and would target AI developers, businesses and governments, according to The Information. Some Apple engineers working on the project believe Nvidia’s NVLink Fusion, which bundles switches, chiplets and software to allow chips from different vendors to communicate at high speed, represents the best available connectivity solution. The product could still be cancelled, The Information noted, and neither Apple nor Nvidia has publicly confirmed the talks.

New Apple (NASDAQ: AAPL) CEO John Ternus, who took the helm earlier this month, was a backer of the server project at its inception roughly a year ago while leading Apple’s hardware engineering division, people familiar with the matter told The Information. His continued support is seen as a key reason the project has momentum.

The project reflects a genuine commercial imperative. Mac was Apple’s fastest-growing product segment in its most recently reported quarter, with revenue surging nearly 29% to $10.4 billion, fuelled by unexpected demand from AI developers snapping up Mac mini and Mac Studio units, per The Information. That surge has created acute supply shortages and exposed the limits of consumer-grade hardware for enterprise AI workloads.

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