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Hewlett Packard Enterprise Debuts End-to-End AI-Native Portfolio for Generative AI

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NVIDIA GTC, Hewlett Packard Enterprise announced updates to one of the industry’s most comprehensive AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications. The updates include:

“To deliver on the promise of GenAI and effectively address the full AI lifecycle, solutions must be hybrid by design,” said Antonio Neri, president and CEO at HPE. “From training and tuning models on-premises, in a colocation facility or the public cloud, to inferencing at the edge, AI is a hybrid cloud workload. HPE and NVIDIA have a long history of collaborative innovation, and we will continue to deliver co-designed AI software and hardware solutions that help our customers accelerate the development and deployment of GenAI from concept into production.”

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“Generative AI can turn data from connected devices, data centers and clouds into insights that can drive breakthroughs across industries,” said Jensen Huang, founder and CEO at NVIDIA. “Our growing collaboration with HPE will enable enterprises to deliver unprecedented productivity by leveraging their data to develop and deploy new AI applications to transform their businesses.”

Announced at SC23, HPE’s supercomputing solution for generative AI is now available to order for organizations seeking a preconfigured and pretested full-stack solution for the development and training of large AI models. Purpose-built to help customers accelerate GenAI and deep learning projects, the turnkey solution is powered by NVIDIA and can support up to 168 NVIDIA GH200 Grace Hopper Superchips.

The solution enables large enterprises, research institutions, and government entities to streamline the model development process with an AI/ML software stack that helps customers accelerate GenAI and deep learning projects, including LLMs, recommender systems, and vector databases. Delivered with services for installation and set-up, this turnkey solution is designed for use in AI research centers and large enterprises to realize improved time-to-value and speed up training by 2-3X.

SOURCE: Businesswire

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