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Pole position

How VAST and NVIDIA can help you win the generative AI race.

Webinar This is no time for business to take a leisurely pit stop, as the rapid increase in generative AI and HPC use-cases across industries and business sectors shows.

More and more enterprises are using generative AI to enhance customer interactions, improve data discovery and streamline operations. But one of the major issues they face is the requirement for advanced infrastructure that integrates high performance storage and accelerated computing to deliver rapid insights from the overwhelming amount of data being generated.

NAS solutions from VAST Data and accelerated computing from NVIDIA can help confront the challenges that the machine learning and deep learning applications and workloads present. Take a look at the Register's latest webinar - Delivering Generative AI in 2023 - hosted by James Hayes in discussion with VAST Data's John Mao, VP, Global Business Development, and NVIDIA's Tony Paikeday, Senior Director of Product Marketing, Artificial Intelligence Systems to learn more.

Hear them undertake an interactive discussion on the key issues facing enterprises leveraging AI, consider the major infrastructure challenges as businesses race to prototype and deploy AI-powered applications into their business models. You'll also get a look at just how VAST Data and NVIDIA can provide AI solutions with validated DCX SuperPOD architectures.

Because provisioning for performance-optimized data storage systems and large scale computing infrastructure is key to serving your AI-powered business initiatives. Collaborating closely, NVIDIA and VAST Data have created the NVIDIA DGX SuperPOD certification – a solution capable of virtually limitless levels of scale and performance that is also simple and resilient in operation. Together they can help any enterprise to set up GPU-powered platforms – computing, networking and storage - that easily enables AI-ready clouds whenever required.

Click here to view the webinar.

Sponsored by VAST Data.

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