Related Topics:
Microsoft Submerging Servers Into-
Korean rack-mounted immersion liquid cooling
Korean firms S-Oil and Global Standard Technology (GST) have teamed up on a new immersion cooling solution for data centers. This article provides an in-depth analysis of how South Korean data centers are tackling this challenge, focusing on the real-world adoption cases of immersion cooling, a technology rapidly emerging as the next-generation solution. The push follows projections that demand for immersion cooling oil will surge as the global artificial intelligence (AI) market. LG Uplus launches cooling demo — The company opens a real-world demo room to test liquid cooling tech for high-density AI workloads at its major data center in Anyang, Korea. The company signed a memorandum of understanding with SNU's College of Engineering and Databean, a firm specializing in. According to Mordor Intelligence, the South Korean data center cooling market size is estimated at US$ 176. 67 million in 2025 and is expected to reach US$ 454.
[PDF Version]
-
Domestic AI Servers Accelerate Entry into the Market
TrendForce's latest research reveals that the surge in demand for AI servers is accelerating the pace at which major US CSPs are developing in-house ASICs, with new iterations being released every one to two years. Search across reports, market insights, and blog stories. Type at least 3 characters to see fast results. According to data from an IDC report reviewed by Reuters, Chinese producers of graphics processing units and. Market Size by Server, by Hardware, by Cooling Technology, by Deployment, by Application, by End Use. projects the global AI server market was valued at USD 128 billion in 2024. 56 billion in 2025, with some forecasts predicting an astonishing rise to USD 1. With AI infrastructure remaining a strategic priority, IDC projects AI infrastructure spending will reach $487 billion in 2026 and surpass $1 trillion by.
[PDF Version]
-
What types of servers are used for deploying AI
AI servers are high-performance computing systems designed to process complex artificial intelligence workloads, including large-scale model training and real-time inference. They provide the hardware environment —. Modern AI models are data-hungry, computation-heavy beasts that need specialized hardware just to function, let alone perform at their best. In this comprehensive guide, we will explore the key factors to consider when selecting an AI server setup, including understanding your AI workload requirements, determining the right. To cover modern requirements, here at ServerMania, we offer a range of options, including colocation for AI infrastructure, managed AI server solutions, and cloud-based AI servers, ensuring organizations can deploy, maintain, and scale AI tasks with maximum efficiency. In this quick guide, we'll. A critical decision for anyone embarking on AI development or deployment is selecting the appropriate server specifications, particularly concerning the central processing unit (CPU), graphics processing unit (GPU), and random access access memory (RAM).
[PDF Version]