AI workload management and orchestration software provider Run:ai has fruitfully collaborated with Nvidia since 2020.
California-based chipmaker Nvidia has announced it agreed to acquire Israeli startup Run:ai, which enables enterprise customers to manage and optimize their artificial intelligence (AI) computing infrastructure.
Run:ai platform enables corporate customers worldwide to manage their data-center-scale GPU clusters. It is built on Kubernetes, the orchestration layer for modern AI and cloud infrastructure. One of the platform’s benefits is that it supports AI deployment workloads across multiple infrastructures, whether on-premise, in the cloud, or hybrid environments.
As of now, NVIDIA will continue to offer Run:ai’s products under the same business model. The firm will also maintain investments in the Run:ai product roadmap as part of NVIDIA DGX Cloud. This AI platform is co-engineered with leading clouds for enterprise developers. It offers an integrated, full-stack service optimized for generative AI.
Run:ai’s solutions are already integrated with NVIDIA DGX, NVIDIA DGX SuperPOD, NVIDIA Base Command, NGC containers, and NVIDIA AI Enterprise software. Thus, NVIDIA DGX and DGX Cloud customers will soon gain access to Run:ai’s capabilities for their AI workloads.
Although the chipmaker didn’t disclose the terms of the deal, Israeli newspaper Calcalist reported that the value of the transaction might stand at about $700 million.
Nvidia’s last major deal in Israel was the $7 billion acquisition of Mellanox Technologies that took place in 2020. Israel is among Nvidia’s top most important markets. The company employs more than 3,200 workers in the country, which is about one-sixth of its entire global workforce.
Nvidia is actively developing innovations in the AI segment. This March, the chipmaker introduced a new generation of artificial intelligence chips and software for running AI models. New AI graphics processors named Blackwell go beyond the traditional microcircuit functions, being more akin to a platform than a standard microchip.
