NVIDIA and Microsoft Azure are collaborating to provide advanced AI infrastructure and software to companies. NVIDIA will display its AI solutions with Microsoft Azure at Microsoft Ignite in Seattle. NVIDIA DGX Cloud, available on Microsoft Azure, enables businesses to train models for generative AI. Microsoft Azure will host NVIDIA Omniverse Cloud, a service that aids businesses in digitalising their operations. NVIDIA GPU-accelerated virtual machines on Azure, powered by NVIDIA H100 Tensor Core GPUs and NVIDIA Quantum-2 InfiniBand networking, offer improved performance for AI workloads.
AI as a Tool for Innovation
Artificial intelligence (AI) has become a crucial element in driving innovation in various sectors. Many organisations are now faced with the task of utilising AI to streamline their operations, enhance their customer offerings, and create new business opportunities. This involves the use of advanced AI infrastructure and software to handle complex workloads.
One of the solutions offered by this collaboration is the NVIDIA DGX Cloud, which is available on Microsoft Azure. This service allows enterprises to train models for generative AI and fuel other advanced applications. This is a significant step in making AI more accessible and usable for businesses.
NVIDIA Omniverse Cloud on Microsoft Azure
In a bid to speed up the digitalisation of enterprise industrial operations, NVIDIA announced that Microsoft Azure will host the NVIDIA Omniverse Cloud. This platform as a service provides businesses with instant access to a full-stack environment to design, deploy, and manage their digitalised operations. This could include building virtual factories or validating autonomous vehicles.
NVIDIA GPU-accelerated Virtual Machines on Azure
Another offering from the collaboration is the NVIDIA GPU-accelerated virtual machines on Azure. These machines, such as the recently announced ND H100 v5-series powered by NVIDIA H100 Tensor Core GPUs and NVIDIA Quantum-2 InfiniBand networking, enable a significant leap in performance and scalability. This is designed to power the most challenging AI training and inference workloads.
Roundtable on Generative AI
In addition to these offerings, NVIDIA and Microsoft hosted a roundtable on generative AI on November 15. The discussion focused on how to choose the right platform for successful generative AI, make AI cost-effective, and more. This event provided valuable insights into the practical application of AI in various industries.
NVIDIA and Microsoft Azure have come together to support these demands by bringing state-of-the-art AI infrastructure and software to companies tackling challenging workloads.
Summary
NVIDIA and Microsoft Azure are collaborating to provide advanced AI infrastructure and software to businesses dealing with complex workloads. This includes the NVIDIA DGX Cloud on Microsoft Azure for training AI models, and the NVIDIA Omniverse Cloud hosted on Microsoft Azure, a service that allows businesses to design, deploy and manage their digital operations.”
- NVIDIA and Microsoft Azure are collaborating to provide advanced AI infrastructure and software to companies dealing with complex workloads.
- NVIDIA will present its AI solutions portfolio with Microsoft Azure at Microsoft Ignite, an event taking place from November 14-17 in Seattle.
- NVIDIA DGX Cloud, available on Microsoft Azure, enables businesses to train models for generative AI and other advanced applications.
- Microsoft Azure will host NVIDIA Omniverse Cloud, a platform that provides businesses with a full-stack environment to design, deploy, and manage their digital operations. This is aimed at accelerating the digitalisation of enterprise industrial operations.
- NVIDIA GPU-accelerated virtual machines on Azure, including the recently announced ND H100 v5-series powered by NVIDIA H100 Tensor Core GPUs and NVIDIA Quantum-2 InfiniBand networking, offer significant improvements in performance and scalability for challenging AI training and inference workloads.
- Microsoft and NVIDIA will host a roundtable on generative AI on November 15, discussing how to choose the right platform for successful generative AI and make AI cost-effective.
