There was no scarcity of predictions over the previous a number of years about how AI will influence the info heart trade and the way information facilities will assist form the evolution of AI. We’ve been instructed, for instance, that AI will result in a surge in energy consumption by information facilities and spur main new information heart building efforts.
Over the course of the previous yr, it has began to turn into clearer which of those predictions and tasks will play out. We now have proof, for instance, about how AI is contributing to information heart firm profitability, in addition to a number of the challenges (like chip shortages) the trade faces in deploying AI workloads on a big scale.
On the identical time, nevertheless, as-yet-unproven projections and predictions about AI’s influence on the info heart trade continued to abound over 2024. There stay many opinions about what’s coming subsequent – like new “edge AI” architectures – and little in the best way of proof demonstrating that these opinions are correct.
For full particulars on these and different information heart tendencies involving AI, right here’s a breakdown of the highest DCN tales on this vein from the previous yr.
A July 2024 report from Moody’s concerning the growth of information heart capability in response to the AI increase was notable not as a result of it predicted the seemingly apparent – that corporations will construct extra information facilities to deal with AI workloads over the approaching years – however as a result of it quantified the projected influence of that growth on information heart operations. Most notably, Moody’s predicted that AI will contribute to a 23 % total enhance in information heart vitality consumption between 2023 and 2028, and that vitality used tied to AI workloads particularly will develop by an annual fee of 43% over the identical interval.
These numbers are predictions, they usually may develop into incorrect. However if you wish to know in quantitative phrases precisely how AI is poised to influence information heart operations, this supply is nearly as good as any.
One other report, launched in September by the Dell’Oro Group, provided quantitative perception into what AI means for information heart spending. It discovered that information heart capital expenditures surged by 46% in simply the second quarter of 2024 – a development that, if it holds, means that AI will gasoline an unlimited enhance in information heart funding and spending over the close to future. The expansion displays not simply AI {hardware} purchases but additionally the ability and cooling programs essential to help AI units in information facilities.
BlackRock additionally chimed in in 2024 with projections for AI’s influence on information heart development. Its numbers had been much less exact, however it predicted that AI information facilities will increase in capability by between 60% and 80% per yr over the following a number of years.
On stability, it’s value noting that the corporate didn’t outline precisely what an “AI information heart” is or the extent to which the growth of information facilities on this class will contribute to total information heart capability. Nonetheless, because the opinion of an organization whose enterprise is to foretell and capitalize on main financial tendencies, BlackRock’s projections about AI’s position in information heart growth are important.
In one other information level that at the least not directly correlates with AI’s position in information heart development, Equinix, which operates information facilities internationally, attributed its 8% enhance in income this yr largely to AI. Not coincidentally, the corporate can be within the midst of quickly increasing its information heart footprint.
Equinix didn’t present particulars about how a lot of its income development was as a result of AI workloads particularly, and its CEO cautioned that it might take time for the trade to really feel the complete weight of AI. Nonetheless, in the event you’re prepared to exit on a limb and assume that correlation implies causation to some extent, it’s an affordable conclusion that the AI increase – which correlates with monetary success this yr for Equinix – is at the least beginning to pay dividends for information heart operators.
One other signal of AI’s influence on information heart enterprise methods was a pivot by information heart operators from amenities that cater to cryptocurrency mining towards ones targeted on AI. That’s the transfer Iris Vitality described to DCN this yr.
This shift makes good sense on condition that curiosity in cryptocurrency has usually waned in recent times and that the identical varieties of infrastructure and units – like GPUs – that excel at crypto-mining additionally work properly as AI {hardware}. However the development is notable all the identical as a result of it means that, at the least to some extent, expanded information heart capability to help AI will come within the type of crypto-mining amenities which can be repurposed for AI, somewhat than brand-new information facilities. On this sense, the repurposing of cryptocurrency information facilities for AI workloads may cut back the quantity of latest information heart investments fueled by the AI increase.
Different notable – albeit not precisely goal – opinions concerning the position of AI in information facilities and past appeared this yr from the CEOs of Nvidia and Meta. Talking at SIGGRAPH this summer time, the executives talked about, amongst different matters, how their corporations are utilizing AI internally – together with to assist handle information heart operations for Nvidia, in response to feedback by Nvidia CEO Jensen Huang.
The dialogue provided few technical particulars, so it’s difficult to attract takeaways about what using AI inside information facilities by corporations like Nvidia and Meta truly entails, or what it could portend for AI’s influence on the best way information facilities function. However it’s nonetheless attention-grabbing that these corporations – each of which promote AI merchandise, in fact, and subsequently have incentive to advance the narrative about AI’s more and more central position in fashionable companies – need to say concerning the inner use of AI.
It’s one factor to increase the capability of information facilities for internet hosting AI workloads. It’s one other to deploy the precise server infrastructure that helps these workloads – and due to the scarcity of high-bandwidth reminiscence (HBM) chips reported this yr, there’s a danger that the growth of AI-friendly information heart area will outpace the expansion of AI-friendly servers. That’s as a result of HBM chips are used to fabricate GPUs, that are often used for AI coaching and inference.
That is an instance of one of many challenges the info heart trade might want to overcome to maintain continued development in response to the AI increase.
Preserving AI infrastructure cool is one other elementary problem that will hinder continued information heart growth. That’s very true as a result of elevated frequency and depth of warmth waves. AI chips produce quite a lot of warmth underneath any circumstances, however dissipating the warmth turns into even more durable when the ambient temperature surrounding a knowledge heart surges as a result of warmth waves.
That is one purpose why progressive information heart cooling applied sciences, which may dissipate warmth in energy-efficient methods, are prone to turn into a key factor in continued information heart growth within the age of AI.
So-called edge AI may contribute to methods for bettering the info heart sustainability within the age of AI. Edge AI means having AI workloads course of information on the community edge as a substitute of in centralized information facilities. Doing so may cut back vitality consumption and enhance efficiency by decreasing the quantity of information transmission required to deploy AI.
On stability, it’s value noting that AI processes like coaching are inclined to require massive quantities of vitality regardless of the place they happen – whether or not on the edge or in a traditional information heart – so edge AI is unlikely to cut back vitality consumption very dramatically. Nonetheless, there could possibly be some tangible sustainability advantages as a result of benefits like decreased warmth focus (and, by extension, decreased vitality consumption by cooling programs), since edge AI infrastructure doesn’t place massive numbers of AI chips in shut proximity to one another.
To supply a deeper dive into what edge AI would possibly seem like in observe, DCN lined one key kind of edge AI use circumstances: Giant Language Fashions (LLMs) deployed on the edge. By working LLMs on edge units like smartphones, companies can cut back the vitality and compute calls for that AI locations on their information facilities. At the moment, benefiting from edge units for this function is difficult as a result of most edge {hardware} is just not optimized for LLMs, however that might change as chip producers design extra AI-friendly processors to be used in units like smartphones.
