Behind the Plot To Break Nvidia's Grip on AI By Targeting Software

An anonymous reader shares a report: Nvidia earned its $2.2 trillion market cap by producing AI chips that have become the lifeblood powering the new era of generative AI developers from startups to Microsoft, OpenAI and Google parent Alphabet. Almost as important to its hardware is the company's nearly 20 years' worth of computer code, which helps make competition with the company nearly impossible. More than 4 million global developers rely on Nvidia's CUDA software platform to build AI and other apps. Now a coalition of tech companies that includes Qualcomm, Google and Intel, plans to loosen Nvidia's chokehold by going after the chip giant's secret weapon: the software that keeps developers tied to Nvidia chips. They are part of an expanding group of financiers and companies hacking away at Nvidia's dominance in AI. "We're actually showing developers how you migrate out from an Nvidia platform," Vinesh Sukumar, Qualcomm's head of AI and machine learning, said in an interview with Reuters. Starting with a piece of technology developed by Intel called OneAPI, the UXL Foundation, a consortium of tech companies, plans to build a suite of software and tools that will be able to power multiple types of AI accelerator chips, executives involved with the group told Reuters. The open-source project aims to make computer code run on any machine, regardless of what chip and hardware powers it. "It's about specifically - in the context of machine learning frameworks - how do we create an open ecosystem, and promote productivity and choice in hardware," Google's director and chief technologist of high-performance computing, Bill Hugo, told Reuters in an interview. Google is one of the founding members of UXL and helps determine the technical direction of the project, Hugo said. UXL's technical steering committee is preparing to nail down technical specifications in the first half of this year. Engineers plan to refine the technical details to a "mature" state by the end of the year, executives said. These executives stressed the need to build a solid foundation to include contributions from multiple companies that can also be deployed on any chip or hardware.

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