Artificial intelligence is surely expected to achieve the unexpected; in every possible way. Here are some of the everyday applications, which you may have not noticed before.
Doing so will make today’s energy-hungry data centers run more efficiently.
For example, they can code an algorithm to quickly complete certain tasks, or even divide resources between jobs.
Therefore, it is virtually impossible for humans to optimize their scheduling algorithms for a particular workload, and as a result, they are often limited to their actual capacity.
In a paper on SIGCOMM, they describe a system that leverages the “reinforcement learning” (RL), a trial-and-error machine-learning technique for making scheduling decisions for specific workloads in specific server clusters.
The results indicate that the system can enable data centers to handle a single workload at a high speed using fewer resources.
“In existing systems, these are hard-coded parameters.









