HPE and Nvidia tailor AI infrastructure to organisations’ needs
HPE and NVIDIA have unveiled a portfolio of "AI Factory" solutions to help organisations implement AI infrastructure tailored to their specific requirements. The partnership addresses different AI ambitions—from frontier model training to high-volume inference and agentic AI—each requiring distinct infrastructure and operational expertise.
The HPE AI Factory portfolio provides three tiers: HPE Private Cloud AI (a turnkey on-premises solution supporting up to 256 GPUs for fine-tuning and inference), HPE AI Factory at-scale (accommodating hundreds to tens of thousands of GPUs for large enterprises), and HPE Sovereign AI Factory (adding advanced security, data residency and compliance features for organisations with strict regulatory requirements). Each solution integrates NVIDIA's accelerated computing with HPE's infrastructure, software and expertise to address compute, networking, storage, security and operational management.
- HPE and NVIDIA launch tiered AI Factory infrastructure for different business needs.
- Solutions range from 256-GPU turnkey systems to sovereign deployments.
- Purpose-built AI infrastructure can match organisations' workloads and compliance requirements.
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Organisations increasingly want to use artificial intelligence to improve their work, but this requires building and managing computer systems specifically designed for AI. This is expensive and technically difficult, requiring specialised equipment, software and expert staff that many organisations don't already have.
NVIDIA and Hewlett Packard Enterprise are two technology companies with experience in providing these systems. NVIDIA makes the specialised computer processors that power AI, whilst HPE builds and manages the broader computer infrastructure that organisations need. Together, they have the expertise to help companies set up AI systems.
Different organisations have different needs when implementing AI. Some want smaller systems for local use, others need much larger setups because they're running ambitious AI projects at scale, and some must follow strict regulations about where their data is stored and how it's protected. A solution that works for one organisation might not work for another, which is why customised approaches matter.
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Originally published by The Register as “Build the right AI factory for your needs: partner for success”.