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HPE and NVIDIA launch AI Factory portfolio for diverse AI needs

HPE and NVIDIA have introduced the HPE AI Factory with NVIDIA portfolio, offering integrated solutions for organisations to build AI infrastructure tailored to their specific requirements.

  • The HPE AI Factory with NVIDIA portfolio provides three options: HPE Private Cloud AI, HPE AI Factory at-scale, and HPE Sovereign AI Factory.
  • These solutions integrate NVIDIA accelerated computing and AI software with HPE infrastructure, software, services, and expertise.
  • The portfolio aims to help organisations design cost-effective AI infrastructure around their mission, scaling with demand and ensuring security.

HPE and NVIDIA have launched the HPE AI Factory with NVIDIA portfolio, designed to help organisations implement AI solutions. The portfolio combines NVIDIA's accelerated computing, networking, and AI software with HPE's infrastructure, software, services, and system deployment expertise.

The offering provides three distinct paths to accommodate varying ambitions and operational models. HPE Private Cloud AI is a turnkey, on-premises platform for fine-tuning, RAG, and inferencing workloads, supporting up to 256 GPUs. For larger operations, HPE AI Factory at-scale supports model builders, service providers, and large enterprises using hundreds to tens of thousands of GPUs, offering centralised control and multi-tenancy.

The third option, HPE Sovereign AI Factory, is an at-scale solution with enhanced operational control, data security, residency, and built-in compliance frameworks. This is intended for large enterprises and organisations with sensitive information requiring strict control within legal, regulatory, or geographic boundaries.

Thierry Pienaar, HPE Fellow, Vice President, and CTO for HPC and AI Sales, stated that customers need an end-to-end infrastructure specifically designed for AI to fully derive value. He added that the portfolio allows enterprises to choose an architecture suited to their current mission and expand it as requirements evolve.

Why this matters: Organisations are seeking integrated solutions to manage the complexities of AI implementation, from model training to high-volume inference, across diverse business needs.

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