Nvidia CEO Jensen Huang made a slew of announcements and revealed new products on Monday that are aimed at keeping the company at the center of artificial intelligence development and computing.
One of the most notable announcements was its new “NVLink Fusion” program, which will allow customers and partners to use non-Nvidia central processing units and graphics processing units together with Nvidia’s products and its NVLink.
Until now, NVLink was closed to chips made by Nvidia. NVLink is a technology developed by Nvidia to connect and exchange data between its GPUs and CPUs.
“NV link fusion is so that you can build semi-custom AI infrastructure, not just semi-custom chips,” Huang said at the Computex 2025 in Taiwan, Asia’s biggest electronics conference.
According to Huang, NVLink Fusion allows for AI infrastructures to combine Nvidia processors with different CPUs and application-specific integrated circuits (ASICs). “In any case, you have the benefit of using the NV link infrastructure and the NV link ecosystem.”
Nvidia announced Monday that AI chipmaking partners for NVLink Fusion already include MediaTek, Marvell, Alchip, Astera Labs, Synopsys and Cadence. Under NVLink Fusion, Nvidia customers like Fujitsu and Qualcomm Technologies will also be able to connect their own third-party CPUs with Nvidia’s GPUs in AI data centers, it added.
According to Ray Wang, a Washington-based semiconductor and technology analyst, the NVLink represents Nvidia’s plans to capture a share of data centers based on ASICs, which have traditionally been seen as Nvidia competitors.
While Nvidia holds a dominant position in GPUs used for general AI training, many competitors see room for expansion in chips designed for more specific applications. Some of Nvidia’s largest competitors in AI computing — which are also some of its biggest customers — include cloud providers such as Google, Microsoft and Amazon, all of which are building their own custom processors.
NVLink Fusion “consolidates NVIDIA as the center of next-generation AI factories—even when those systems aren’t built entirely with NVIDIA chips,” Wang said, noting that it opens opportunities for Nvidia to serve customers who aren’t building fully Nvidia-based systems, but are looking to integrate some of its GPUs.
“If widely adopted, NVLink Fusion could broaden NVIDIA’s industry footprint by fostering deeper collaboration with custom CPU developers and ASIC designers in building the AI infrastructure of the future,” Wang said.
However, NVLink Fusion does risk lowering demand for Nvidia’s CPU by allowing Nvidia customers to use alternatives, according to Rolf Bulk, an equity research analyst at New Street Research.
Nevertheless, “at the system level, the added flexibility improves the competitiveness of Nvidia’s GPU-based solutions versus alternative emerging architectures, helping Nvidia to maintain its position at the center of AI computing,” he said.
Nvidia’s competitors Broadcom, AMD, and Intel are so far absent from the NVLink Fusion ecosystem.
Other updates
Huang opened his keynote speech with an update on Nvidia’s next-generation of Grace Blackwell systems for AI workloads. The company’s “GB300,” to be released in the third quarter of this year, will offer higher overall system performance, he said.
On Monday, Nvidia also announced the new NVIDIA DGX Cloud Lepton, an AI platform with a compute marketplace that Nvidia said will connect the world’s AI developers with tens of thousands of GPUs from a global network of cloud providers.
“DGX Cloud Lepton helps address the critical challenge of securing reliable, high-performance GPU resources by unifying access to cloud AI services and GPU capacity across the NVIDIA compute ecosystem,” the company said in a press release.
In his speech, Huang also announced plans for a new office in Taiwan, where it will also be building an AI supercomputer project with Taiwan’s Foxconn, officially known as Hon Hai Technology Group, the world’s largest electronics manufacturer.
“We are delighted to partner with Foxconn and Taiwan to help build Taiwan’s AI infrastructure, and to support TSMC and other leading companies to advance innovation in the age of AI and robotics,” Huang said.
Source: https://www.cnbc.com/
