AMD to Acquire Open Source AI Software Expert Nod.ai

AMD today announced the  signing of a definitive agreement to acquire Nod.ai to expand the company’s open AI software  capabilities. The addition of Nod.ai will bring an experienced team that has developed an  industry-leading software technology that accelerates the deployment of AI solutions optimized  for AMD Instinct™ data center accelerators, Ryzen™ AI processors, EPYC™ processors,  Versal™ SoCs and Radeon™ GPUs to AMD. The agreement strongly aligns with the AMD AI  growth strategy centered on an open software ecosystem that lowers the barriers of entry for  customers through developer tools, libraries and models.  

“The acquisition of Nod.ai is expected to significantly enhance our ability to provide AI  customers with open software that allows them to easily deploy highly performant AI models  tuned for AMD hardware,” said Vamsi Boppana, senior vice president, Artificial Intelligence  Group at AMD. “The addition of the talented Nod.ai team accelerates our ability to advance  open-source compiler technology and enable portable, high-performance AI solutions across  the AMD product portfolio. Nod.ai’s technologies are already widely deployed in the cloud, at the  edge and across a broad range of end point devices today." 

“At Nod.ai, we are a team of engineers focused on problem solving — quickly – and moving  at pace in an industry of constant change to develop solutions for the next set of problems,” said  Anush Elangovan, co-founder and CEO, Nod.ai. “Our journey as a company has cemented our  role as the primary maintainer and major contributor to some of the world's most important AI  repositories, including SHARK, Torch-MLIR and OpenXLA/IREE code generation technology.  By joining forces with AMD, we will bring this expertise to a broader range of customers on a  global scale.” 

Nod.ai delivers optimized AI solutions to top hyperscalers, enterprises and startups. The  compiler-based automation software capabilities of Nod.ai’s SHARK software reduce the need  for manual optimization and the time required to deploy highly performant AI models to run  across a broad portfolio of data center, edge and client platforms powered by AMD CDNA™,  XDNA™, RDNA™ and “Zen” architectures.