The impact of AI on data centres

Before we start, let's get pedantic: at this point in time artificial intelligence is a purely theoretical concept. True AI, a sentient computer capable of initiative and human interaction, remains within the realm of science fiction. The AI research field is full of conflicting ideas, and it’s not clear whether we can actually build a machine that can replicate the inner workings of the human brain.
And yet, being a part of the IT industry, you’ll have seen proclamations that one product or another delivers AI functionality. Just a few years ago, the same functionality would be called data analytics.
This being said, machine learning and related techniques are already producing some impressive results, so this post will look at the potential near-future implications of AI research – if we’re being optimistic.
In the data centre
The impact of AI on data centres can be divided into two broad categories – the impact on hardware and architectures, as the users start adopting AI-inspired technologies, and the impact on the management and operation of the facilities themselves.
We’ll start with the first category: turns out that machine learning and services like speech and image recognition require a new breed of servers, equipped with novel components such as Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs). All of these require massive amounts of power, and produce massive amounts of heat.
Nvidia, the world’s largest supplier of graphics chips, has just announced DGX-2, a 10U box for algorithm training that includes 16 Volta V100 GPUs along with two Intel Xeon Platinum CPUs and 30TB of flash storage. DGX-2 delivers up to two Petaflops of compute, and consumes a whopping 10kW of power – more than an entire 42U rack of traditional servers.
And Nvidia is not alone in pushing the envelope on power density: DGX-2 is actually a reference design, and server vendors have been given permission to iterate and create their own variants, some of which might be even more power-hungry. Meanwhile, Intel has just confirmed rumours that it’s working on its own data centre GPUs – expected to hit the market in 2020.
As power densities go up, so does the amount of heat that needs to be removed from the servers, and this will inevitably result in growing adoption of liquid cooling. Dumping $200,000 worth of equipment into a tub of mineral oil or bringing water pipes into the rack might not seem like a good idea today, but these approaches might offer the only way to cool servers of the future.
As a consequence, AI research will require data centres engineered for higher power densities, with additional cooling and very, very strong floors.
For the data centre
But machine learning is also useful in management of the data centre, where it can help optimize energy consumption and server use.
For example, an algorithm could spot under-utilized servers, automatically move the workloads and either switch off idle machines to conserve energy, or rent them out as part of a cloud service, creating an additional revenue stream.
Google has famously claimed that it used AI to reduce its data centre Power Usage Effectiveness rating by 15 percent, saving millions on electricity. While the company is reluctant to share this technology, other businesses are bringing similar capabilities mainstream.
American software vendor Nlyte has just partnered with IBM to integrate Watson – perhaps the most famous ‘cognitive computing’ product to date – into its Data Centre Infrastructure Management (DCIM) products.
“Behold, a new member of the data centre team, one that never takes a vacation or your lunch from the breakroom,” quipped Amy Benett, North American marketing lead for Watson IoT.
Beyond management, AI could improve physical security by tracking individuals throughout the data centre using CCTV, and alerting its masters when something looks out of order.
I think it’s a safe bet to say that every DCIM vendor will eventually offer some kind of AI functionality. Or at least something they call AI functionality.
Source: virtusdatacentres

Latest Jobs
-
- Senior Presales Consultant | Managed Security Services | London
- London
- N/A
-
Senior Presales Consultant – Managed Security Services Location: London-commutable (Hybrid) A well-established cyber consultancy is seeking a Senior Presales Consultant to drive growth across its managed security services / advisory portfolio. This hybrid role bridges commercial and technical expertise supporting solution design, shaping customer proposals, and guiding conversations from scoping through to delivery. Key experience: Background in managed security services, including SOC operations and threat detection Strong knowledge of cloud and on-prem security tooling (SIEM, EDR, IAM) Penetration testing Proven ability to translate technical concepts into clear business value Confident in customer-facing engagements and pre-sales delivery Experience contributing to bids, proposals, and RFI/RFP responses To find out more contact me on 07884666351 Visa sponsorship is unfortunately not available for this role.
-
- Senior SOC Engineer - Microsoft | Splunk. Permanent. London
- London
- N/A
-
Senior SOC Engineer – Hybrid London Type: Full-Time A well-established cyber security provider is seeking a Senior SOC Engineer to strengthen its managed services function. This role is ideal for someone with a strong operational background in SIEM and EDR tools who can confidently lead customer onboarding, fine-tune detection strategies, and act as a senior point of contact for technical escalations. You will need to be SC clearable. Bonus points if you have SC clearance currently. You will be responsible for ensuring smooth integration of new clients into the service, optimising alerting capabilities and delivering meaningful outcomes during investigations. This is a hands-on position, working closely with internal teams and external stakeholders to maintain robust security operations across multiple environments. Prior experience in a cyber-focused MSP or MSSP Strong hands-on capability with platforms such as Microsoft Sentinel, Defender for Endpoint, or similar Proficiency in scripting and query languages such as KQL or PowerShell Knowledge of detection logic, investigation workflows, and cloud-based infrastructure Confident communicator with strong documentation and reporting skills Apply today for more information.