The basic line is that data center operators have a wide range of AI/ML alternatives, with more on the way as the technology becomes more affordable and advanced.
FREMONT, CA: Data center operators can use Artificial Intelligence (AI) and Machine Learning (ML) technology to increase uptime, reduce energy consumption, promptly detect possible problems, and protect against cyber-attacks.
Here are two approaches to incorporating machine learning into your data center:
AI is evolving, which means that its capabilities are expanding as the cost curve falls. As a result of these two trends, data center providers will include AI/ML into more of their products. AI/ML can be applied to a data center’s mechanical and electrical equipment to provide actionable insights and automation, allowing the operator to save money. This necessitates combining classic physics-based modeling approaches with cutting-edge machine learning techniques based on data from IoT devices. Both machine learning and physics-based modeling offer advantages. Combining the two allows you to address complicated data center issues involving mechanical and electrical equipment by combining the best of both disciplines.
The need for anywhere, anytime access to apps and services such as autonomous vehicles, smart cities, advanced manufacturing, AR/VR gaming, and related industry 4.0 use cases are skyrocketing thanks to 5G and related industry 4.0 use cases. As a result, latency is no longer a viable option. As a result, edge data centers and multi-access edge compute (MEC) capabilities are becoming more prominent. It is now possible to execute AI/ML workloads near to the user where data is generated, and gain real-time insights and experiences offered via highly responsive and contextually aware apps, thanks to compact, inexpensive, and powerful hardware in edge data centers.
Leverage digital twins
Datacenter digital twins are physics-based, allowing them to mimic the performance of a new configuration rather than relying just on data. For example, a detailed 3D representation of the data center space, architecture, mechanical and engineering systems, cooling, power connectivity, and the raised floor’s weight-bearing capability is included in a physics-based digital twin. This allows operators to predict, visualize, and quantify the impact of each data center change before deployment, giving them the confidence to make informed decisions.
The digital twin combined with artificial intelligence can assist IT teams in dealing with the increasing complexity of current data center environments. However, even while data centers are the crucial performance centers of the digital world, maintaining them still involves manual labor and in-depth, professional knowledge.