Artificial Intelligence (AI) is one of the most powerful technological forces in this era and, while it began in the data centre, it's moving quickly to the edge. NVIDIA's Charlie Boyle says that one of the biggest things the sector is seeing – which started at the end of 2020 but accelerated into 2021 – is the idea of an AI centre of excellence for companies and institutions. "There's a big change from what we were seeing a few years ago. Previously, when people worked on AI, it would tend to start small, getting some results and would grow over time," he explains. "We are engaging with a lot of customers today, who have realised that starting very small and growing organically may not get them the results they need in the next couple of years. Before, an individual researcher or a small team may procure one or two systems, a little bit of infrastructure, some networking and storage. "Now, we are seeing that more at a strategic level inside of the company where, in order to achieve even basic results, management is realising it needs a critical mass of infrastructure to carry out the experiment to drive the applications that they need.

With cloud technology advancing at a brisk clip, artificial intelligence has become something of a double-edged sword for data centers. Advanced algorithms are placing new demands on servers, requiring heightened power, space and cooling in data centers. But they're also part of the solution, with software boosting efficiency and raising the bar for data center operators. "With businesses of every size looking to leverage AI, particularly medium-sized businesses that can't afford extensive in-house data center networks, the demand for modernized data centers will only increase," Nuclear Research analyst Daniel Elman said. "Of course, a large part of that increase will be serviced by the largest cloud vendors ... but it leaves opportunity for other players to enter the market as well to meet the growing demand."

If you keep track of industry trends at all, then I bet your newsfeed has been filled with exciting stories and bold predictions about artificial intelligence (AI), machine learning (ML), and neural networks. With hyperbolical headlines such as, "How Artificial Intelligence Will Self-manage the Data Center" and "Is 2018 When Machines Take Over?", I'm sure many people are mentally rolling their eyes as they click to the next story. And companies sometimes want to grab on to it and claim it for their own before things are fully baked. I believe in the power of AI to make data centers better.

So, you want to scale your computing muscle to train bigger deep learning models. Can your data center handle it? According to Nvidia, which sells more of the specialized chips used in machine learning than any other company, it most likely cannot. These systems often consume so much power, a conventional data center doesn't have the capacity to remove the amount of heat they generate. It's easy to see how customers without infrastructure that can support a piece of Nvidia hardware is a business problem for Nvidia.

Data center operators deploying tools that rely on machine learning today are benefiting from initial gains in efficiency and reliability, but they've only started to scratch the surface of the full impact machine learning will have on data center management. Machine learning, a subset of Artificial Intelligence, is expected to optimize every facet of future data center operations, including planning and design, managing IT workloads, ensuring uptime, and controlling costs. By 2022, IDC predicts that 50 percent of IT assets in data centers will be able to run autonomously because of embedded AI functionality. "This is the future of data center management, but we are still in the early stages," Rhonda Ascierto, VP of research at Uptime Institute, said. Creating smarter data centers becomes increasingly important as more companies adopt a hybrid environment that includes the cloud, colocation facilities, and in-house data centers and will increasingly include edge sites, Jennifer Cooke, research director of IDC's Cloud to Edge Datacenter Trends service, said. "Moving forward, relying on human decisions and intuition is not going to approach the level of accuracy and efficiency that's needed," Cooke said.

If you keep track of industry trends at all, then I bet your newsfeed has been filled with exciting stories and bold predictions about artificial intelligence (AI), machine learning (ML), and neural networks. With hyperbolical headlines such as, "How Artificial Intelligence Will Self-manage the Data Center" and "Is 2018 When Machines Take Over?", I'm sure many people are mentally rolling their eyes as they click to the next story. And companies sometimes want to grab on to it and claim it for their own before things are fully baked. I believe in the power of AI to make data centers better.

Artificial intelligence is set to play a bigger role in data-center operations as enterprises begin to adopt machine-learning technologies that have been tried and tested by larger data-center operators and colocation providers. Today's hybrid computing environments often span on-premise data centers, cloud and collocation sites, and edge computing deployments. And enterprises are finding that a traditional approach to managing data centers isn't optimal. By using artificial intelligence, as played out through machine learning, there's enormous potential to streamline the management of complex computing facilities. AI in the data center, for now, revolves around using machine learning to monitor and automate the management of facility components such as power and power-distribution elements, cooling infrastructure, rack systems and physical security.