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With many businesses striving to optimize their energy consumption to meet sustainability goals, AI represents a challenge.
So how can businesses help?
Offering the same performance to meet todays workloads, they have been designed with energy efficiency in mind.
Not only does this consolidation save space, but it also reduces the carbon footprint of the data center.
For this reason, businesses can increase uptime and capacity, making way for more bandwidth-hungry workloads.
Adjusting server performance to workloads minimizes power consumption and means that servers are used more efficiently.
This allows the organisation to spot where energy is being wasted and reduce consumption.
Critical workloads will receive the necessary resources, while reducing overprovisioning in other areas.
This far exceeded its goal of sending 3% or less.
Think about the use cases of AI and the specific outcome you want them to achieve.
Different types of AI will have different energy consumption costs.
Dont get swept up by the hype of advanced deep learning systems that can do it all.
These are expensive and use a lot of data, meaning they have a high carbon footprint.
Instead, take a focused approach that is trained on a much smaller quantity of data.
We’ve listed the best NAS devices.
