Intel confirmed the purchase of 214.7 million shares in a securities filing Monday (Dec. 29), concluding a deal first announced in September.
A report on the purchase by Reuters characterizes it as a significant lifeline for Intel, following years of missteps and costly production capacity expansions which sapped its finances.
The announcement comes days after the Federal Trade Commission (FTC) announced that regulators had cleared the way for the planned investment, viewed as a major endorsement of Intel by the world’s most valuable company.
The two companies are also launching a partnership centered around product development, with plans to collaborate on multiple generations of customized data center and personal computing products to “accelerate applications and workloads across hyperscale, enterprise, and consumer markets.”
Nvidia also recently acquired talent and tech from Groq, a maker of custom-built inference chips. A company spokesperson framed the deal this way in a statement last week to PYMNTS: “We haven’t acquired Groq. We’ve taken a non-exclusive license to Groq’s IP and have hired engineering talent from Groq’s team to join us in our mission to provide world-leading accelerate computing technology.”
Groq wrote on its blog post that with this agreement, the companies hope to expand access to high-performance, low-cost inference, a term for the stage in which a trained model processes new data and produces results. When a customer service chatbot replies to a query or an AI system analyzes a financial document, that is an example inference at work.
“While training creates the model by processing vast datasets to learn patterns, inference applies that learned knowledge to perform specific tasks at scale,” PYMNTS wrote earlier this year. “As enterprises deploy AI systems that manage thousands or millions of requests daily, inference becomes the dominant operational challenge and cost driver.”
Also this month, Nvidia introduced its Nemotron 3 family of open models designed to power transparent, efficient and specialized agent-centric artificial intelligence across industries.
As reported here, developers and enterprises can access these models, associated data and tooling to create and customize AI agents for tasks that include coding and reasoning as well as complex workflow automation.
“Open-source AI models are large pretrained neural networks whose weights and code are publicly available for download, inspection, modification and redistribution,” the report said.
“By contrast with closed or proprietary models controlled by a single provider, open models enable developers, researchers and enterprises to adapt the model to specific needs, verify behavior, and integrate the technology into their systems without restrictive licensing.”
