This is AI generated summarization, which may have errors. For context, always refer to the full article.
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. “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 Magro, told Reuters in an interview. Google is one of the founding members of UXL and helps determine the technical direction of the project, Magro said.
Since its launch in September, UXL has already begun to receive technical contributions from third parties that include foundation members and outsiders keen on using the open-source technology, the executives involved said. Intel’s OneAPI is already useable, and the second step is to create a standard programming model of computing designed for AI.