NVIDIA has acquired Israeli AI startup Run:ai, aiming to enhance its AI ecosystem and provide open-source software to users worldwide.
NVIDIA, a dominant player in the artificial intelligence hardware sector, has successfully completed its acquisition of the Israeli AI startup Run:ai. Founded in 2018 by Omri Geller and Ronen Dar, Run:ai specializes in software designed to enhance the performance of AI hardware. Following the acquisition, NVIDIA has announced its intentions to make Run:ai’s software open source, allowing users to utilize the tools even on hardware not manufactured by NVIDIA.
This strategic move aligns with NVIDIA’s ongoing efforts to fortify its offerings within the AI ecosystem while also fostering the global AI community through accessible open-source technologies. By distributing Run:ai’s software broadly, NVIDIA aims to optimise AI computing efficiency and aid a diverse range of developers and organisations, regardless of their choice of hardware. This approach is anticipated to significantly enhance AI performance and widen the availability of advanced AI tools.
NVIDIA has not disclosed specifics regarding the transaction itself; however, an Israeli publication previously reported that the acquisition was valued at approximately $700 million. Notably, this acquisition marks NVIDIA’s second substantial investment in the Israeli tech sector, following its $7 billion purchase of Mellanox Technologies in 2020.
NVIDIA continues to lead the AI hardware market, consistently achieving substantial revenues, reportedly tens of billions of dollars each quarter. The integration of Run:ai is expected to bolster NVIDIA’s suite of software and hardware solutions, further expanding its reach within the industry. The company had established a collaborative relationship with Run:ai since 2020, and now, being part of NVIDIA’s larger ecosystem, Run:ai is set to enhance the efficiency and performance of AI applications across various sectors.
Source: Noah Wire Services
- https://blogs.nvidia.com/blog/runai/ – Corroborates NVIDIA’s acquisition of Run:ai and the integration of Run:ai’s software into NVIDIA’s ecosystem.
- https://blogs.nvidia.com/blog/runai/ – Provides details on Run:ai’s specialization in software for enhancing AI hardware performance and its collaboration with NVIDIA since 2020.
- https://developer.nvidia.com/run-ai – Explains Run:ai’s role in managing and optimizing AI compute infrastructure, including its Kubernetes-based workload management.
- https://developer.nvidia.com/run-ai – Details the key features and benefits of Run:ai, such as fair-share scheduling and dynamic resource allocation.
- https://www.run.ai/guides/machine-learning-engineering/ai-chips – Describes how Run:ai automates resource management and workload orchestration for machine learning infrastructure.
- https://www.run.ai/guides/machine-learning-engineering/ai-chips – Highlights the capabilities of Run:ai in managing AI chips and optimizing GPU resource utilization.
- https://blogs.nvidia.com/blog/runai/ – Mentions the acquisition’s impact on NVIDIA’s offerings and its plan to support a broad ecosystem of third-party solutions.
- https://developer.nvidia.com/run-ai – Discusses how Run:ai’s platform bridges the efficiency of High-Performance Computing and the simplicity of Kubernetes.
- https://blogs.nvidia.com/blog/runai/ – Notes that NVIDIA will continue to offer Run:ai’s products under the same business model and invest in the Run:ai product roadmap.
- https://www.run.ai/guides/machine-learning-engineering/ai-chips – Explains how Run:ai simplifies machine learning infrastructure pipelines, enhancing data scientists’ productivity and model quality.