Enterprises deploying AI inference need to choose carefully to limit costs and protect their data.
Even before data center operators move to higher voltages, rising power densities are increasing the risks faced by electricians.
Although cloud platforms often offer the lowest cost for AI inference, on-premises deployment may be preferable due to application architecture, data locality and control requirements.
Project approval will hinge on local benefit guarantees
Where to deploy AI inference: pricing tool
Capacity allocation and the next generation of AI-era KPIs
Optimizing Sites for Human Performance and Staff Success
Network Advisory: Current State of Digital Twins
Emerging life safety challenges in modern data centers
electricity tariff cost to the opex of data centre
carbon emission reference figures
Supply Chain Issues with Data Center components: Is anyone finding More... issues with…
The struggle between AI and net-zero is becoming visible
Why inference will become a ubiquitous IT workload
Musk's moonshot project faces astronomical challenges
Next-gen GPUs may not need chillers — but data centers do
Liquid cooling will not outgrow its high-density niche
Coolant distribution units can complicate commissioning
Ireland's new grid rules signal shift in data center roles
New power architectures to reshape data center design
Giant data center power plans reach extreme levels
Resiliency will be re-examined, but few will compromise
EU power providers urged to protect grids from data centers
What cloud sovereignty really means
IT power thresholds can incentivize server inefficiency
Digital twins and DCIM: why data quality must come first
As capacity demands surge, operators rethink cloud strategies
