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5 Things to Know About AI & Data Centers

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AI in Data Centers

Artificial Intelligence, also known as AI, is not a new concept.  It has been the subject of many sci-fi novels and movies over the last 4 decades or so – and it has been around far longer than that! AI is now seeing a renaissance of sorts as machine learning, and thus AI, becomes a more tangible reality.  All things associated with AI, including machine learning, deep learning, neural networks, and more require significant amounts of algorithmic data.  As the technology continues to develop and become more common-place, this will significantly impact the energy and data storage load that is placed on data centers and that means that now is the time for data centers to prepare.  Below, we take a closer look at 5 things that everyone, but particularly those in the data center and technology industries should know.  

5 Things to Know About AI & Data Centers

1. AI Is For All Data Centers

  • Some data centers may assume AI will not be impacting them any time soon (‘that’s tomorrow’s problem!’) or that it won’t impact them at all (‘that is for other data centers because they are bigger, serve a different industry, or that is for data centers that are —fill in the blank—).  And while, certainly, large data centers can possibly see the most benefits from AI implementation, smaller data centers can as well. The reality is that AI is for ALL data centers.  Yes, all data centers should anticipate the impact AI will have on them because it is virtually inevitable that AI will impact them. Gone are the days of simple machine learning, AI is leveraging machine learning in a new way, along with deep learning, to provide insight and better management of resources.  That is something that both small and large data centers alike need.  In fact, for smaller data centers with proportionately small resources, deep learning that leads to AI being able to perform intelligence tasks can actually save money and resources that your data center may not otherwise be able to without AI.

2. AI Will Dramatically Impact DCIM

  • Evaluating DCIM efficiency and effectiveness is an ongoing task for DCIM managers or other data center personnel.  The goal is streamlining for efficiency while maintaining quality of service provided.  As AI permeates more and more data centers, it is important to look at the relationship between AI data center management software and DCIM. Data Center Knowledge explains the intersection of AI enabled data management software and DCIM, “The end game for data center infrastructure management (DCIM) software is that it eventually enables self-managing, or fully autonomic, data centers. The hope is that AI-driven management software (likely cloud-based) will monitor and control IT and facilities infrastructure, as well as applications, seamlessly and holistically – potentially across multiple sites. Cooling, power, compute, workloads, storage, and networking will flex dynamically to achieve maximum efficiency, productivity, and availability.”

3. AI Will Improve Data Center Security

  • Due to the IoT, we are concerned nor more than ever before with data security.  What we know is that any data security solution must be robust, complex, multi-layered, and scalable.  Finding software that achieves that at the various levels needed for the volume and sensitivity of data used by data centers can be rather challenging. The key to minimizing cyber attacks is anticipation, early detection, and prevention.  To do that requires a significant amount of time and effort, particularly if the process is inefficient. If that analysis takes a long time, it may not detect the threat until it is already too late.  AI algorithms can be running all day, every day, to analyze and predict behaviors which is an excellent first line of defense against cyber attacks.  And, not only are they continuously running, they are far more quick than other detection and prevention methods.  By being more accurate and quick than other methods, AI has poised itself as an invaluable tool in the protection of data security.

4. AI Will Impact Personnel Employed by Data Centers

  • Anytime someone reads a headline about the impact of AI on data centers, the logical first question is – will AI eliminate many jobs in data centers?  The short answer – yes.  But, the long answer is far more important for this answer.  The long answer is that, while AI will eliminate many of the traditional data center jobs we have had in the past and still have today, AI will also create a multitude of new jobs – far more than it eliminates!  This is good news because that means there will still be many ‘human’ jobs in data centers.  It is important to note, thought, that this also means new skillsets will be required.  If you are in the technology industry or work in a data center and plan to for the next 10+ years, it would be wise to learn as much about AI and its use in data centers as you possibly can.  Staying ahead of technological advancements positions yourself, and your data center, for thriving in a new era rather than flailing, or worse, failing.

5. AI Will Make Data Centers More Energy Efficient

  • Energy efficiency is a massive priority in the data center industry.  Some of the largest data centers consume more energy in a year than some small countries – that is a lot of energy.  And, because AI has a multitude of algorithms, it has more data and that means more energy expenditure by data centers.  So then, how exactly will AI improve data center energy efficiency?  As AI continues to improve and evolve, its ability to make sophisticated decisions improves. And not only can AI make more intelligent decisions than humans (in some circumstances), it can also make them more quickly.  Both of these things lead to energy savings.  Data Center Knowledge points to the case of Google and how AI was able to save energy better than humans in the data center, “Under a recent tornado watch, the AI system managing the cooling plant at one of Google’s data centers in the Midwest changed the plant’s settings in a way which the facility’s human operators found counterintuitive. After closer scrutiny, however, it did what had to be done to save energy under those specific circumstances…The company is now aggressively rolling out what Kava referred to as a “tier-two automated control system.” Instead of simply making recommendations, this tier-two system makes all the cooling-plant tweaks on its own, continuously, in real-time. The first system, developed by Gao as a “20-percent project” and later with involvement from Google’s DeepMind AI team, could shave up to 40 percent off a facility cooling system’s total energy use. The new fully automated version is saving about 30 percent annually, and the company expects further improvements.”



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