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How to Apply Machine Learning in Your Data Center

AI is maturing, which implies that its capabilities are expanding while its costs are decreasing.
FREMONT, CA: Artificial Intelligence (AI) and Machine Learning (ML) technologies are a tried and true method for data center operators to increase uptime, minimize energy use, discover possible dangers promptly, and fight against cyber-attacks.
Let's see few ways to implement machine learning in the data center
Embedded AI
By integrating AI/ML technology in their products, data center providers make it easier for their clients to start adopting AI/ML. In addition, because most AI use cases are highly specialized today, these AI chips may get taught for a specific job such as pattern recognition, natural language processing, network security, robotics, and automation.
AI is maturing, which implies that its capabilities are expanding while its costs are decreasing. These two trends will enable data center companies to include AI/ML into a broader range of their products.
Use AI/ML for the new construction and retrofits
Building information modeling (BIM) and building performance simulation (BPS) technologies, for example, should be used by operators to integrate AI/ML into their planning and construction processes. In addition, its guidance is applicable to retrofit initiatives, such as allowing predictive maintenance at an existing plant.
Leverage digital twins
Digital twins should also be included in data center architecture and administration so that the 3D virtual replica may replicate its physical behavior under any operational situation. In addition, it has virtual representations of the facility's building blocks: power, cooling, and the IT system components from all significant OEMs.
The digital twin brings all the stakeholders together to strategize and take control of your data center's performance and business effect. All in one system, the digital twin gives powerful visibility to decrease operational risk, alleviate process bottlenecks, and enable the study of "what-ifs." In addition, the digital twin combined with AI can assist IT teams in dealing with the increasing complexity of current data center settings. While data centers are the essential performance hubs at the heart of the digital world, operations still need a significant amount of physical labor and in-depth, specialized knowledge to keep things operating.
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