AWS Trainium and Graviton chips: How Amazon powers AI and cloud
As AI shifts from answering questions to taking actions, agentic workloads are driving new CPU demand. AWS Trainium chips are purpose-built for training and running AI models at lower
Artificial Intelligence (AI) Servers – Intel
AI servers play a critical role in enabling AI use cases from edge to cloud. By strategically combining AI hardware components, AI servers support essential AI workloads across the entire pipeline—from
Transforming Server Architecture for AI Workloads
Learn how AI workloads are reshaping server architecture with accelerators, CXL memory pooling, high-speed interconnects, and advanced cooling.
Building the AI Server
AI/ML demands are reshaping servers. Explore how CPUs, GPUs, FPGAs and AI accelerators drive performance for workloads like deep learning and predictive analytics.
What is an AI Server? AI Server Architecture Explained
Learn what AI servers are and how they power artificial intelligence. Complete guide to AI server components, architecture, and requirements for ML and AI.
What is an AI server?
AI servers are built for massive parallelization, repeatedly executing the same mathematical operations across enormous datasets. An AI server executes workloads by coordinating compute, memory,
With a systems approach to chips, Microsoft aims to tailor everything
Much like building a house lets you control every design choice and detail, Microsoft sees the addition of homegrown chips as a way to ensure every element is tailored for Microsoft
A Jargon-Free Guide on How AI Server Architecture Works
Whether you''re deploying AI in your business, tinkering with a project, or just want to understand the tech shaping our world, this guide discusses what goes into AI server architecture,
AI Infrastructure | Google Cloud
What is AI Hypercomputer? An architecture combining purpose-built hardware, open software, and flexible consumption. Each component is carefully integrated to work well together, improving...
AI Chips for Data Centers and Cloud 2025-2035: Technologies,
Graphics processing units (GPUs) and other AI chips have been instrumental in driving this growth of artificial intelligence, providing the compute needed for deep learning within data centers and cloud
Micro-Modular & Edge DC
Prefabricated micro-modular data centers and edge pods, scalable from 5 to 50 racks, ready for 5G and edge AI workloads.
Immersion & Liquid Cooling
Single-phase immersion cooling tanks and direct-to-chip liquid cooling switches, achieving PUE below 1.1.
AI Servers & Racks
GPU-accelerated AI servers, high-density server racks, and network cabinets optimized for AI/ML workloads.
DCIM/EMS & Cable Bridge
Real-time data center infrastructure management, plus overhead cable trays and fiber bridges for structured cabling.