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8 Hot AI And Machine Learning Tools For Data Centers

Here are eight ways machine learning and artificial intelligence tools are being leveraged in data centers to solve some of the IT world’s biggest issues around data, cybersecurity and server optimization.

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Automate Workload Movements And Management

A slew of new AI tools are being launched to automate the movement of workloads to the most efficient IT infrastructure, whether it be in a data center, at the edge or in a hybrid cloud environment.

AI is striving to transform workload management to reduce time-consuming and manual tasks by data center operators, boost workload efficiency and cut down costs of having workloads in inefficient IT environments such as public clouds versus on-premise. Artificial intelligence helps allocate workloads in a more effective manner than traditional automation solutions by enable customers to become more flexible and scale faster.

Startups are sprouting up around AI for workload management such as DLabs, Redwood Software and Tidal Software. For example, Tidal Software is becoming a leading provider of enterprise workload AI solutions that orchestrate the execution of complex workflows across systems, applications and data enter environment. Tidal’s entire product portfolio revolves around leveraging AI to orchestrate complex IT workflows, optimize workload automation activities, and provide centralized management automation for all workloads.

 
 
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