The cost and complexity of deploying large-scale GPU clusters for generative AI training will drive many enterprises to the public cloud. Most enterprises will use pre-trained foundation models, to reduce computational overheads.
Not all generative AI applications will require large and dense infrastructure footprints. This complicates AI power consumption projections and data center planning.
Enterprises have much enthusiasm for AI, interviews and workshops by Uptime Intelligence suggest, but this is tempered by caution. Most hope to avoid disruptive, expensive or careless investments.
Enterprises have various options on how and where to deploy their AI training and inference workloads. This report explains how these different options balance cost, complexity and customization.
To meet the demand driven by AI workloads, a new breed of cloud provider has emerged, delivering inexpensive GPU infrastructure as a service. Their services are highly demanded today, but longer-term, the market is ripe for consolidation.
Many speculate that AI and automation might replace humans in data center jobs but there is little evidence to support this line of thought. The data center industry has characteristics that researchers believe may protect against worker displacement
This report provides a regional view of the results from the Uptime Institute Global Data Center Survey 2024 and highlights some of the different challenges and strategies of data center owners and operators across the globe.
Trust in AI as a tool for data center operations has declined sharply in the past three years. It is possible to control for the factors that drive mistrust β and see better outcomes when employees interact with AI-based systems.
The data center industry's largest and most influential survey results are in! Join us as we discuss the 14th Annual Uptime Global Data Center Survey 2024 which reveals an industry that is expanding, and is also planning for major technological,β¦
The 14th edition of the Uptime Institute Global Data Center Survey highlights the experiences and strategies of data center owners and operators in the areas of resiliency, sustainability, efficiency, staffing, cloud and AI.
Many data center operators are unaware that digitizing process documentation can impact staff performance. Understanding human psychology enables team leaders to create more effective digital versions of procedural documents.
Many data centers struggle to achieve maximum capacity and optimal cooling, resulting in troublesome hot spots. Advances in cooling optimization software have addressed this complexity and could be the answer.
The 14th edition of the Uptime Institute Global Data Center Survey highlights the experiences and strategies of data center owners and operators in the areas of resiliency, sustainability, efficiency, staffing, cloud and AI. The attached dataβ¦
Data center infrastructure management (DCIM) software is evolving and improving. This report discusses where DCIM has made most progress, and why it is now considered a viable and worthwhile investment.
This report outlines the characteristics of machine learning (ML) applications, describes production use cases for ML-based software in data center M&O, and profiles several vendors offering AI-based functionality in their products.