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]
-
Technical Challenges of AI Servers
AI's massive compute demands, paired with expectations for efficiency, speed, and scalability, are pushing traditional architectures to their limits. Such is the pace of innovation in AI systems that every year since 2020 could have easily been deemed “The Year of AI. ” There will undoubtedly be countless more “Years of AI” as the technology continues to take root in the processes that orchestrate societies and businesses around the world. The industry is rapidly transitioning to 800G and 1. As AI continues to extend its reach into various industries, the demand for robust IT infrastructure capable of training AI, and. The term AIOps (Artificial Intelligence for IT Operations), introduced by Gartner in 2016, defines an approach to IT infrastructure management using artificial intelligence. The combination of Big Data and ML (machine learning) technologies makes it possible to automate processes and increase the. The increasing demand for advanced AI capabilities, particularly in areas like generative video, is placing unprecedented strain on server infrastructure, leading to discussions about "OpenAI Servers Melting: AI's Technical Challenges.
[PDF Version]