[es-emea] AI Imperatives

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.

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"

Be Efficient

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.

Be First

A meticulous plan is necessary to differentiate between calculated risks and reckless decisions. Understand these challenges to approach infrastructure innovation with confidence.

Be Confident

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.

Be Future-ready

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.

See challenges to risk management

AI Imperatives

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See infrastructure efficiency challenges

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See challenges for future-readiness

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See technical challenges to being first

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See challenges to being transformative

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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.

Critical Infrastructure challenges:

Imperativos de la IA

A través de nuestro proceso de experiencia del usuario de Vertiv, que integra entrevistas a clientes en profundidad, extensas pruebas técnicas de concepto y colaboración técnica con partners tecnológicos líderes, Vertiv ha seleccionado una colección de imperativos clave de infraestructura de IA que comparten diseñadores, desarrolladores y operadores actuales y futuros de fábricas de IA.

Ser transformador

Las empresas están aprovechando la IA para transformar productos, servicios y participación del cliente. Este cambio exige reformas en los modelos operativos y la infraestructura, afrontando estos desafíos
críticos de cara.

Consulta los chalanges para ser transformador

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Sé el primero

Para avanzar rápidamente en la innovación de productos y experiencias de clientes, es crucial abordar la gestión independiente de sistemas de alimentación y refrigeración. Superar estos desafíos puede conducir a una ventaja de primer impulsor.

Mira los desafíos técnicos para ser el primero

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Ser eficiente

El despliegue eficiente del capital es crucial para la competitividad de costes a la vez que equilibra la potencia de procesamiento de la IA y el impacto medioambiental es esencial para abordar estos desafíos conocidos como la "paradoja de la eficiencia de la IA"

Mira los desafíos de eficiencia de la infraestructura

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Ten confianza

A meticulous plan is necessary to differentiate between calculated risks and reckless decisions. Understand these challenges to approach infrastructure innovation with confidence.

Mira los desafíos de la gestión de riesgos

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Prepárate para el futuro

El crecimiento explosivo de la IA y las demandas informáticas de alto rendimiento requerirán que los centros de datos gestionar densidades de rack superiores a 100kW ¿Estás preparado? Prepara tu centro de datos para un futuro de alta potencia.

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Mira los desafíos para la preparación para el futuro