AI Imperatives
Critical Infrastructure challenges:
Retrofitting existing data center infrastructure in a transformative way.
Accommodating rack power densities >100kW and hardware >5,000lbs.
Deploying liquid and hybrid air-liquid cooling.
Understanding liquid distribution is as critical as power distribution.
Ensuring power availability and intelligent grid interaction.
Critical Infrastructure challenges:
Designing power and cooling paths independently and not as a single system.
Assessing multi-vendor qualifications, dependencies, and technical specifications.
Adopting new technologies and market entrants that lack scalability and global supply chain.
Delivering significantly more field installation work that is costly, time-consuming, and non-repeatable.
Critical Infrastructure challenges:
Leveraging existing infrastructure investments with robust technical design experience.
Addressing constraints in delivering operational efficiency with densities accelerating >33x.
Avoiding over-provisioning and stranded capacity when considering fault tolerance.
Blending new and existing technologies without common language and controls.
Deploying and maintaining AI factories anywhere in the world.
Critical Infrastructure challenges:
Combining new and existing technologies by deeply understanding what is technically possible.
Getting the most from existing infrastructure investments when retrofitting for AI.
Planning today's AI factory with future transformations in mind as densities continues to accelerate.
Maintaining a robust service and maintenance network with experience, footprint, and trusted performance.
Designing to use cases with different risk strategies in mind, i.e., Training vs. Inference
Critical Infrastructure challenges:
Future-proofing the infrastructure investment, mitigating costly future upgrades.
Designing for power and cooling scalability that can leap, not just grow.
Tackling sustainability challenges today and exponentially grow in scope in the future.
Partnering with technically and financially viable players that can support into the future.
Collaborating with players investing in ER&D and are closely aligned with technology leaders.
Through our Vertiv User Experience process, which integrates in-depth customer interviews, extensive technical proofs-of-concept, and technical collaboration with leading technology partners, Vertiv has curated a collection of key AI infrastructure imperatives that current and future designers, developers, and operators of AI factories share.
Be Transformative
Companies are leveraging AI to transform products, services, and customer engagement. This shift demands overhauls in operating models and infrastructure, facing these critical challenges head-on.
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Be First
To make quick progress in innovating products and customer experiences, it's crucial to address the separate management of power and cooling systems. Overcoming these challenges can lead to a first mover advantage.
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Be Efficient
Efficient capital deployment is crucial for cost competitiveness while balancing AI's processing power and environmental impact is essential for addressing these challenges known as the "AI efficiency paradox"
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Be Confident
A meticulous plan is necessary to differentiate between calculated risks and reckless decisions. Understand these challenges to approach infrastructure innovation with confidence.
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Be Future-ready
The explosive growth of AI and high-performance computing demands will require data centers to handle rack densities exceeding 100kW. Are you ready? Prepare your data center for a high-powered future.
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