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Posición de poste

Nodo de origen: 2685389

Seminarios Web Este no es el momento para que las empresas se detengan tranquilamente, como lo demuestra el rápido aumento de los casos de uso de IA generativa y HPC en todas las industrias y sectores comerciales.

Cada vez más empresas utilizan IA generativa para mejorar las interacciones con los clientes, mejorar el descubrimiento de datos y agilizar las operaciones. Pero uno de los principales problemas que enfrentan es el requisito de una infraestructura avanzada que integre el almacenamiento de alto rendimiento y la computación acelerada para brindar información rápida a partir de la abrumadora cantidad de datos que se generan.

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 - Brindando IA generativa en 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.

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