Category Archives: Artificial Intelligence

element14, the Development Distributor, has published new research on the Internet of Things (IoT) which confirms strong adoption of Artificial Intelligence (AI) within IoT devices, alongside new insights on key markets, enablers and concerns for design engineers working in IoT.

AIoT is the major emerging trend from the survey, demonstrating the beginning of the process to build a true IoT ecosystem. Research showed that almost half (49%) of respondents already use AI in their IoT applications, with Machine Learning (ML) the most used technology (28%) followed by cloud-based AI (19%). This adoption of AI within IoT design is coupled with a growing confidence to take the lead on IoT development and an increasing number of respondents seeing themselves as innovators. However, it is still evident that some engineers (51%) are hesitant to adopt AI due to being new to the technology or because they require specialized expertise in how to implement AI in IoT applications.

Other results from element14s second Global IoT Survey show that security continues to be the biggest concern designers consider in IoT implementation. Although 40% cited security as their biggest concern in 2018 and this has reduced to 35% in 2019, it is still ranked significantly higher than connectivity and interoperability due to the type of data collected from things (machines) and humans, which can be very sensitive and personal. Businesses initiating new IoT projects treat IoT security as a top priority by implementing hardware and software security to protect for any kind of potential threat. Ownership of collected data is another important aspect of security, with 70% of respondents preferring to own the data collected by an edge device as opposed to it being owned by the IoT solution provider.

The survey also shows that although many engineers (46%) still prefer to design a complete edge-to-cloud and security solution themselves, openness to integrate production ready solutions, such as SmartEdge Agile, SmartEdge IIoT Gateway, which offer a complete end-to-end IoT Solution, has increased. 12% more respondents confirmed that they would consider third party devices in 2019 than 2018, particularly if in-house expertise is limited or time to market is critical.

A key trend from last years survey results has continued in 2019 and survey results suggest that the growing range of hardware available to support IoT development continues to present new opportunities. More respondents than ever are seeing innovation coming from start-ups (33%, up from 26%), who benefit from the wide availability of modular solutions and single board

computers available on the market. The number of respondents adopting off-the-shelf hardware has also increased to 54% from 50% in 2018.

Cliff Ortmeyer, Global Head of Technical Marketing for Farnell and element14 says: Opportunities within the Internet of Things and AI continue to grow, fueled by access to an increasing number of hardware and software solutions which enable developers to bring products to market more quickly than ever before, and without the need for specialized expertise. This is opening up IoT to new entrants, and giving more developers the opportunity to innovate to improve lives. element14 provides access to an extensive range of development tools for IoT and AI which provide off-the shelf solutions to common challenges.

Despite the swift integration of smart devices such as Amazons Alexa and Google Home into daily life, evidencing a widespread adoption of IoT in the consumer space, in 2019 we saw a slight shift in focus away from home automation with the number of respondents who considered it to be the most impactful application in IoT in the next 5 years reducing from 27% to 22%. Industrial automation and smart cities both gained, at 22% and 16% respectively, underpinned by a growing understanding of the value that IoT data can bring to operations (rising from 44% in 2018 to 50% in 2019). This trend is witnessed in industry where more manufacturing facilities are converting to full or semi-automation in robotic manufacturing and increasing investment in predictive maintenance to reduce production down times.

The survey was conducted between September and December 2019 with 2,015 respondents participating from 67 countries in Europe, North America and APAC. Responses were predominantly from engineers working on IoT solutions (59%), as well as buyers of components related to IoT solutions, Hobbyists and Makers.

element14 provides a broad range of products and support materials to assist developers designing IoT solutions and integrating Artificial Intelligence. Products are available from leading manufacturers such as Raspberry Pi, Arduino and Beagleboard. element14s IoT hub and AI pages also provide access to the latest products for development and insights and white papers to support the design journey. Readers can view an infographic covering the full results of the element14 Global IoT Survey at Farnell in EMEA, Newark in North America and element14 in APAC.

For more information, visit http://www.element14.com

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New research on adoption of Artificial intelligence within IoT ecosystem - ELE Times

When applying for a new job, candidates may well find that the use of artificial intelligence (AI) tools is involved at some point in the recruitment process. New recruitment businesses and technology are entering the market, setting up entirely automated initial conversations with candidates to help them find the right vacancy for their skill set, saving time for applicant and recruiter alike.

CV screening is also becoming more prevalent, with AI screening and tracking tools being used to quickly analyse CVs to ascertain whether the individual has the qualifications and experience necessary for the role for example, burger chain Five Guys is said to be utilising such technology.

Unilever recently hit the headlines when it announced that, instead of human recruiters, it uses an AI system to analyse video interviews. Candidates record interviews on their phone or laptop, and the system scans candidates language, tone and facial expressions from the videos, assessing their performance against traits that are considered to indicate job success at Unilever.

But it is not just the recruitment stage where AI and people analytics are being used by businesses performance management is another targeted area. Amazon is leading this charge the company was issued with two patents in the US for a wristband for tracking the performance of workers in their warehouse, which would mean that staff receive a little buzz if they place a product near or in the wrong inventory location.

It is also alleged that Amazon uses a computer system to automatically generate warnings or terminations to employees, when their productivity (or lack of) warrants it.

The benefits of such technology for employers are countless and clear, including costs savings, efficiency, and the purported removal of human unconscious bias and prejudice. However, the use of AI in the workplace has come under scrutiny and has posed serious ethical and legal questions, including whether AI itself could in fact be biased.

Another important aspect when implementing AI in the workplace is its relationship with data protection laws such as the EUs General Data Protection Regulation (GDPR). So, what data protection considerations should an employer make when considering the introduction of AI technology?

The use of AI for processing personal data will usually meet the legal requirement for completing a DPIA.

A DPIA enables the business to analyse how the AI plans will affect individuals privacy, and ensures the company can assess the necessity and proportionality of its technology.

As the UK Information Commissioners guidance confirms, the deployment of an AI system to process personal data needs to be driven by the proven ability of that system to fulfil a specific and legitimate purpose, not just by the availability of the technology.

The DPIA should demonstrate that the applicable purposes the AI is being used for could not be accomplished in another reasonable way. In doing so, organisations need to think about and document any detriment to data subjects that could follow from bias or inaccuracy in the algorithms and data sets being used.

A business cannot simply process personal data because it wishes to do so data can only be processed where one of the legitimate grounds or conditions of processing has been met. There are various bases, including performance of a contract, compliance with a legal obligation, consent and legitimate business interests. For the processing of sensitive personal data (such as health data), the bases are even more limited.

Before using AI or people analytics in the workplace, employers will first need to consider what data is being processed by such activity and second what legal basis can be relied upon in processing the data in that way. If they do not have a legal basis, the data cannot be processed.

One of the key principles of GDPR is transparency, requiring businesses to provide individuals with mandatory information about the processing of their personal data, including the reason why it is being processed, the legal basis, who it will be shared with and how long it will be retained. Employers will need to update their privacy notices to ensure anyone subject to the AI technology is made aware of its use.

The privacy notice needs to be concise and intelligible, using clear and plain language this will be particularly difficult when including a complex AI system, as businesses will need to provide a meaningful explanation of the technology to meet the transparency principle of GDPR. Opaque or complex descriptions of the tech may result in contention or pushback from the employees and candidates affected.

GDPR prohibits instances of computer says no and contains the right for data subjects not to be subjected to a decision based solely on automated processing, which has a legal or similarly significant impact on them. Its aim is to protect individuals against the risk that a potentially damaging decision is taken without human intervention, and will therefore likely capture a recruitment result made without any human input.

There are specific exceptions when automated decision-making is permitted, including where explicit consent was given, contractual necessity, or where authorised by law. Where such an exception is being relied upon, such as with the consent of a candidate, the business must still implement further safeguarding measures, including permitting the individual to request human intervention or to contest the decision.

Employers will need to ensure that their automated technology is being lawfully used, before relying on its output.

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Dont forget to consider GDPR when using artificial intelligence in the workplace - ComputerWeekly.com

Many AI researchers roll their eyes when seeing this headline:Stephen Hawking warns that rise of robots may be disastrous for mankind. And as many havelost count of how many similar articles theyveseen.Typically, these articles are accompanied by an evil-looking robot carrying a weapon, and they suggest we should worry about robots rising up and killing us because theyve become conscious and/or evil.On a lighter note, such articles are actually rather impressive, because they succinctly summarize the scenario that AI researchers dontworry about. That scenario combines as many as three separate misconceptions: concern about consciousness, evil, androbots.

If you drive down the road, you have a subjective experience of colors, sounds, etc. But does a self-driving car have a subjective experience? Does it feel like anything at all to be a self-driving car?Although this mystery of consciousness is interesting in its own right, its irrelevant to AI risk. If you get struck by a driverless car, it makes no difference to you whether it subjectively feels conscious. In the same way, what will affect us humans is what superintelligent AIdoes, not how it subjectively feels.

The fear of machines turning evil is another red herring. The real worry isnt malevolence, but competence. A superintelligent AI is by definition very good at attaining its goals, whatever they may be, so we need to ensure that its goals are aligned with ours. Humans dont generally hate ants, but were more intelligent than they are so if we want to build a hydroelectric dam and theres an anthill there, too bad for the ants. The beneficial-AI movement wants to avoid placing humanity in the position of those ants.

The consciousness misconception is related to the myth that machines cant have goals.Machines can obviously have goals in the narrow sense of exhibiting goal-oriented behavior: the behavior of a heat-seeking missile is most economically explained as a goal to hit a target.If you feel threatened by a machine whose goals are misaligned with yours, then it is precisely its goals in this narrow sense that troubles you, not whether the machine is conscious and experiences a sense of purpose.If that heat-seeking missile were chasing you, you probably wouldnt exclaim: Im not worried, because machines cant have goals!

I sympathize with Rodney Brooks and other robotics pioneers who feel unfairly demonized by scaremongering tabloids,because some journalists seem obsessively fixated on robots and adorn many of their articles with evil-looking metal monsters with red shiny eyes. In fact, the main concern of the beneficial-AI movement isnt with robots but with intelligence itself: specifically, intelligence whose goals are misaligned with ours. To cause us trouble, such misaligned superhuman intelligence needs no robotic body, merely an internet connection this may enable outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand. Even if building robots were physically impossible, a super-intelligent and super-wealthy AI could easily pay or manipulate many humans to unwittingly do its bidding.

The robot misconception is related to the myth that machines cant control humans. Intelligence enables control: humans control tigers not because we are stronger, but because we are smarter. This means that if we cede our position as smartest on our planet, its possible that we might also cede control.

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Benefits & Risks of Artificial Intelligence - Future of Life ...

The Historical Hype Cycle of AI

Before talking about the current and projected impact of AI in education and other industries, Ramsey explained the concept of the AI winter.

He showed a graph on the historical hype cycle of AI that featured peaks and drops over a 70-year period.

There was a big peak in the mid-1960s, when there was an emergence of symbolic AI research and new insights into the possibility of training two-layer neural networks. A resurgence came in the 1980s with the invention of certain algorithms for training three-plus layer neural networks.

The graph showed a drop in the mid-1990s, as the computational horsepower and data did not exist to develop real-world applications for AI a situation he calls an AI winter. We are in the middle of another resurgence today, he said.

There has been a huge increase in the amount of data and computer power that we have available, sparking research, Ramsey said. People have been able to start inventing algorithms and training not just three-layer neural networks but a 100-layer one.

The question now is where we will go next, he said. His answer? We will sustain progress, leading to true or strong AI the point at which a machines intellectual capability is functionally equal to a humans.

The number of researchers working on this, the amount of money thats being spent on this and the amount of research publications its all growing, he said. And where Google is right now is on a plateau of productivity because were using AI in everything that we do, at scale.

MORE ON EDTECH:Learn how data-powered AI tools are helping universities drive enrollment and streamline operations.

During his presentation, Ramsey showed an infographic that featured what machine learning could look like across a students journey through higher education, starting from their college search and ending with employment.

For example, he said, colleges and universities can apply machine learning when targeting quality prospective students to attend their schools. They can even automate call center operations to make contacting prospective students more efficient and deploy AI-driven assistants to engage with applicants in a personalized way, he said.

Once students are enrolled, they can also useAI chatbotsto improve student support services, assisting new students in their adjustment to college. They can leverage adaptive learning technology topredictperformance as they choose a path through school, and they can tailor material to their knowledge levels and learning styles.

For example, a machine learning algorithm helped educators at Ivy Tech Community College in Indianapolis identify at-risk students and provide early intervention, Ramsey said.

Ivy Tech shifted toGoogleCloud Platform, which allowed the school to manage 12 million data points from student interactions and develop aflexible AI engineto analyze student engagement and success. For instance, a student who stops logging in to their learning management system or showing up to class would be flagged as needing assistance.

The predictions were 83 percent accurate, Ramsey said. It worked quite well, and they were actually able to save students from dropping out, which makes a big difference because their funding is based on how many students they have, he said.

As students near graduation and start their job searches, schools can also use AI to understand career trends and match them to a students competencies and skills. Machine learning can be used to better understand job listings and a jobseekers intent, matching candidates to their ideal jobs more quickly.

At the end of the day, what were doing with these technologies is trying to understand who we are and how our minds work, Ramsey said. Once we fully understand that, we can build machines that function in the same way, and the possibilities are endless.

Originally posted here:

A 5-Year Vision for Artificial Intelligence in Higher Ed - EdTech Magazine: Focus on Higher Education

Updated: May 25, 2018:

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Artificial Intelligence is Starting to Shape the Future of the Workplace - JD Supra

Travel industry is slowly embracing the artificial intelligence in their network so that they can improve their services and provided travelers with a customized experience.

FREMONT, CA:In several industries, the vital transformations have already been racked up by science and artificial intelligence (AI). The travel industry is not an exception to it as there also many business verticals that have been affected by AI. It is not easy to define AI precisely, but here is some information about the immunity that the travel industry is creating for an artificial industry.

The business process and customer services in every dominant industry have significantly developed with the assistance of artificial intelligence. There are several AI software extensively used among the sectors likeMachine Learning, Chatbots, Internet of Things, and Neural Networks. However, among this considerable list, new software has also been added known as the Travel AI, and it will be extremely beneficial for the travel industry. The various uses of AI among the travel industry and travelers.

Virtual Reality

It is time for travel companies to eliminate the traditional concept of paper brochures because VR headsets can provide travelers a real-time feeling of the rooms and the areas surrounding the hotel. The virtual assistant can make the experience of the travelers easy by improving the conversion rates, a high degree of customer experience, and even personalize the travel experience.

The VR technology is also helping the AI-powered in-room assistance as they are developing the travel and hospitality services by speeding up the process of travel booking and delivering a personalized guest experience.

VR for the Travelers

The travelers can also surf hotels, book a room, get tips from the other tourist, and even check the latest tariffs with the help of virtual assistants.

Machine Learning

The ML helps in tracking the travel preferences of the customers, along with enhancing customer services by providing real-time hospitality. The travel industry can also benefit from the robotic technology that uses ML and speech recognition to provide travel information to travelers.

ML for the Travelers

With machine learning, travelers do not have to plan their trip because the computer can do it. The computer will assist the customers to book for the destination that they want to visit, along with every place and the most recommended food in that area.

AI Algorithms

AI algorithms are mostly used for gathering, authenticating, and interpreting the data so that the travel companies can understand the preferences of the customers. The AI will help the travel industry to conclude the pricing outlay, sales, customers' preferences, and the other methods through which they can increase their profit margins.

AI is suitable for the travel companies because it can appropriately perform the data sorting rather than human conducting it as it may contain many errors.

AI algorithms for the Travelers

With the assistance of AI algorithms, the visitors can mechanically get the things they want without even calling for the room service in a hotel.

Chatbots

The chatbots help the business travelers to offer the quickest response time, which is not even possible for the humans to match. The traditional way of customer representative manually replying to the inquiries in the comment of social media posts, websites, and blogs does not work anymore.

Chatbots can easily automate the response. The initial inquiries that customers do to gain information and the feedback from them are effectively managed with the help of chatbots.

Chatbots for the Travelers

The chatbots can be powered with the help of instant messaging apps and social media for providing time-saving services to the customers while they are traveling.

The use of the technology of AI is rapidly increasing in the travel industry because of its own merits and the benefits that it provides. Although AI is still new in the travel and hospitality industry, it offers several user-friendly experiences that make it exceptional.

See Also: Top Travel and Hospitality Solution Companies

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How Artificial Intelligence is Transforming the Travel Industry - CIOReview

The use of artificial intelligence is now the norm in many industries, from integrating the technology in autonomous vehicles for safety, to AI algorithms being used to improve advertising campaigns. But, by using it in healthcare, could it also help us predict the outbreak of a virus such as the COVID-19 coronavirus?

Since the first cases were seen at the end of December 2019, coronavirus has spread from Wuhan, China, to 34 countries around the world, with more than 80,000 cases recorded. A hospital was built in 10 days to provide the 1,000 beds needed for those who had fallen victim to the virus in Wuhan 97 per cent of cases reported are in China.

The World Health Organisation (WHO) has said the world should prepare for a global coronavirus pandemic. The virus can be spread from person to person via respiratory droplets expelled when an infected person coughs or sneezes. According to the WHO: "Common signs of infection include respiratory symptoms, fever, cough, shortness of breath and breathing difficulties. In more severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure, and even death."

AI developers have suggested that the technology could have been used to flag irregular symptoms before clinicians realise there is a developing problem. AI could alert medical institutions to spikes in the number of people suffering from the same symptoms, giving them two to four weeks' advance warning which in turn could allow them time to test for a cure and keep the public better informed.

As the virus continues to spread, AI is now being used to help predict where in the world it will strike next. The technology sifts through news stories and air traffic information, in order to detect and monitor the spread of the virus.

Excerpt from:

Could artificial intelligence have predicted the COVID-19 coronavirus? - Euronews

Big names in technology, including Amazon, Microsoft, and IBM, worked with healthcare industry groups to developa standard for the use of artificial intelligence in healthcare.

Convened by the Consumer Technology Association (CTA), a working group made up of 52 organizations set out to create a common language so industry stakeholders can better understand AI technologies.

Thestandard, which was released Tuesday,has been accredited by theAmerican National Standards Institute (ANSI).

Across-the-Board Impact of an OB-GYN Hospitalist Program

A Denver facility saw across-the-board improvements in patient satisfaction, maternal quality metrics, decreased subsidy and increased service volume, thanks to the rollout of the first OB-GYN hospitalist program in the state.

The CTA working groupwas created a year ago to develop some standardization on definitions and characteristics of healthcare AI.

Healthcare organizations involved in the project include the American Medical Association,Doctor on Demand, Livongo, Ginger, AdvaMed,American Telemedicine Association, Fitbit, soon to be owned by Google, and Humana, thefirst payer to jointhe CTA last September.

It's part of the CTAs new initiative on AI and is the first in several steps the CTAplans to help create a foundation forimplementingmedicaland health caresolutions built onAI.

RELATED:Investors poured $4B into healthcare AI startups in 2019

This standard creates a firm base for the growing use of AI in our health caretechnology that will better diagnose diseases, monitor patients recoveries and help us all live healthier lives, said Gary Shapiro, president and CEO, CTA. This is a major first stepconvening some of the biggestplayers in the digital health worldto help create a more efficient health care system and offer value-based health care to Americans.

AI-related termsareused in differentways,leading toconfusionespecially in thehealth care industry, including telehealth and remote patient monitoring.

The healthcare AI standard developed by the working groupprovides a foundation of definitions to understand AI and common terminology. The goal in creating the standard is to foster "a better understanding AI technologiesandcommon terminologysoconsumers, tech companies and care providers can better communicate, develop and use AI-basedhealth care technologies," the CTA said.

So far, common terminologyhasdefinedthe intent of useand thatsone of the most significant challenges in developing standard applications of AI, saidRene Quashie, VP,policy andregulatoryaffairs,digitalhealth,CTA. As health systemsand providersuse AI toolssuch asmachine learning todiagnose, treat and manage disease, theres an urgent need to understand and agree on AI concepts for consistent use.This standard does exactly that.

Among the definitions, thestandard includesdebatedtermssuch as assistive intelligence, which the group defined as a category of AI software that informs or drives diagnosis or clinical management of a patient with the healthcare provider makingthe ultimate decisions before clinical action is taken.

RELATED:Healthcare CEOs say AI progress stymied by high costs, privacy risks

Other definitions include terms like de-identified data, synthetic data, remote patient monitoring, and patient decision support system.

As the healthcare system deals with clinician shortages, an aging population and the persistence of chronic diseases in the US, technologically driven solutions, such as AI, will increasingly be used to meet clinician and patient needs, the group notes.

As AI is increasingly used fordecision support and decision making, healthcare professionals will need to be able to take ownership, apply judgment and empathy.

"Transparency and a common language will be key to enable the proper and safe functioning of AI," said Pat Baird, regulatory head of global software standards at Philips and co-chair of the working group.

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Amazon, Microsoft team up with Consumer Technology Association on healthcare AI standards - FierceHealthcare

Political polarization is ripping America apart. References to a second American civil war no matter how far-fetched reveal a bitterly divided nation. Indeed, the Founding Fathers worst nightmare is coming to pass.

For all of its promise, technology bears much of the blame for fracturing America. For one, social media platforms create powerful echo chambers that feed us a nonstop diet of one-sided, hyper-partisan news and commentary. This dangerous phenomenon where our beliefs are constantly reinforced and rarely challenged is not unique to liberals or conservatives. Instead, it is a function of technology capitalizing on an ever-expanding cultural and social divide.

But what if technology could be harnessed to reverse this corrosive effect on American society and its underlying cause? Moreover, at a time when factual news reporting is all too often immediately dismissed as fake, we are in desperate need of voices broadly respected by all Americans.

Enter Americas Founding Fathers and machine learning.

Despite the passage of centuries, Americans of all political stripes continue to invoke the ideas and writings of the Founders. Few figures hold more sway or command more respect among political pundits, politicians and everyday patriots than Adams, Hamilton, Jay, Jefferson, Madison and Washington.

While it may seem far-fetched on its face, what if artificial intelligence and machine learning could bring these titans of history back to life to weigh in on the challenges facing the United States today?

Artificial intelligence, in short, amounts to providing machines with enough data to make decisions or predictions without human input. Autonomous cars, for example, drive around American cities gathering real-time experience to inform decision-making. The challenge with driverless cars, however, is that staggering amounts of data are required to predict the many surprises that these machines are likely to encounter on the road.

But when it comes Americas Founding Fathers, we have all the data that we need in their writings, speeches and legislative records to resurrect them through machine learning. Indeed, the Founders discussed and debated the most contentious issues from the media to taxation, education, religion and beyond that America confronts today. Human nature, after all, ensures that history tends to repeat itself.

Bringing the Founders back through artificial intelligence processes would bestow enormous benefits. For one, the addition of such revered and respected voices would allow us to regain some semblance of civility in public discourse. Indeed, it would be difficult to denigrate Jefferson or Madisons take on contemporary issues such as the national debt or impeachment as partisan fake news.

Most importantly, the most corrosive effects of hyper-partisan, ratings-driven media outlets and the social media platforms that enable them would be blunted, reining in the extreme division and political polarization gripping America.

To be sure, significant challenges would accompany such an ambitious venture. The process of coding the Founders writings and records into mathematical vectors digestible by machines could prove complex, stretching current capabilities to their limitations. The same is true for the all-important task of accurately translating the issues dividing America today into machine-readable data. But the good news is that significant groundwork has been done in this arena: Artificial intelligence and neural networks already conduct political predictions as well as complex, issue-based analyses.

With little potential for profit, securing adequate funding for such an endeavor will also prove challenging. But thanks to initiatives such as Googles Artificial Intelligence for Social Good and grants supporting AI-enabled fact-checking, there is reason for optimism. Indeed, the inherently ethical and positively disruptive nature of such technology may attract broad support from an ideologically diverse cross-section of civically-minded institutions and individuals.

Ultimately, the Founding Founders lasting gift to the American people is a treasure trove of wisdom on civil discourse, shared values and sound governance. At a time when America finds itself dangerously divided, we must not hesitate to harness the Founding Fathers collective legacy for the betterment of the nation that they cherished so dearly.

Marik von Rennenkampff served as an analyst with the U.S. Department of States Bureau of International Security and Nonproliferation, as well as an Obama administration appointee at the U.S. Department of Defense. Follow him on Twitter @MvonRen.

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How to save America with artificial intelligence | TheHill - The Hill

Vertiv EMEA president Giordano Albertazzi looks back on data center expansion in the Nordics and the regions role as an efficient best execution venue for the future.

At the start of the new year its natural to look to thefuture. But its also worth taking some time to think back to the past.

Last year was not only another period of strong data center growthglobally, and in the Nordic region specifically, but also the end of a decadeof sustained digital transformation.

There have been dramatic shifts over the last ten years butthe growth in hyperscale facilities is one of the most defining and one withwhich the Nordic region is very well acquainted.

According to figures from industry analysts Synergy Researchthe total number of hyperscale sites has tripled since 2013 and there are nowmore than 500 such facilities worldwide

And it seems that growth shows no signs of abating. Accordingto Synergy, in addition to the 504 current hyperscale data centers, a further151 that are at various stages of planning or building.

A good numberof those sites will be sited in the Nordics if recent history is anything to goby. The region has already seen significant investment from cloud andhyperscale operators such as Facebook, AWS and Apple. Google was also one ofthe early entrants and invested $800 million inits Hamina, Finland facility in 2010. It recently announced plans to invest a further $600 million in an expansion ofthat site.

I was lucky enough to speak at the recent DataCloud Nordicsevent at the end of last year. My presentation preceded Googles country manager,Google Cloud, Denmark and Finland, Peter Harden, who described the companysgrowth plans for the region. Hamina, Finland is one of Googles mostsustainable facilities thanks in no small part to its Nordics location whichenables 100% renewable energy and innovative sea water cooling.

Continuing that theme of sustainability, if the last decadehas been about keeping pace with data demand, then the next ten years will beabout continued expansion but importantly efficient growth in the right locations,using the right technology and infrastructure. The scale of growth beingpredicted billions of new edge devices for example will necessitate asustainable approach.

That future we at Vertiv, and others, believe will be basedaround putting workloads where they make most sense from a cost, risk, latency,security and efficiency perspective. Or as industry analysts 451 Research putsit: TheBest Execution Venue (BEV). (a slightlyunwieldy term but an accurate one). BEV refers to the specific ITinfrastructure an app or workload should run on cloud, on-premise or at theedge for example but could also equally apply to geographic location of datacenters.

In that BEV future, the Nordics will become increasingly important for hosting a variety of workloads but the sweet-spot could be those that are less latency sensitive high performance compute (HPC) for example and can therefore benefit from the stable, renewable and cheap power as well as the abundance of free cooling. Several new sub-sea cables coming online over the near future will also address some of the connectivity issues the region has faced.

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A recent study by the Nordic Council of Ministers estimatesthat approximately EUR 2.2 bn. have been invested in the Nordics on initiateddata centre construction works over the last 12 to 18 months (2018). Mainlywithin hyperscale and cloud infrastructure. This number could exceed EUR 4 bn.annually within the next five to seven years because of increasing marketdemand and a pipeline of planned future projects.

Vertiv recently conducted some forward-looking research thatappears to reinforce the Nordics future potential. Vertiv first conducted itsData Center 2025 research back in 2014 to understand where the industry thoughtit was headed. In 2019, weupdated that study to find out how attitudes had shifted in the interveningfive years a half way point if you will be between 2014 and 2025.

The survey of more than 800 data center experts covers a range of technology areas but lets focus on a few that are important and relevant to the Nordics.

We mentioned the edge a little earlier when talking about BEV.Vertiv has identified fourkey edge archetypes that cover the edge use cases that our experts believewill drive edge deployments in the future. According to the 2025 research, ofthose participants who have edge sites today, or expect to have edge sites in2025, 53% expect the number of edge sites they support to grow by at least 100%with 20% expecting an increase of 400% or more.

So along with providing a great venue for future colo and cloud growth, the Nordics, like other regions, is also likely to see strong edge growth. That edge demand will require not only new data center form-factors such as prefabricated modular (PFM) data center designs but also monitoring and management software and specialist services.

Another challenge around edge compute, and the core for thatmatter, is energy availability and increasingly, access to clean, renewableenergy.

The results of the 2025 research revealed that respondentsare perhaps more realistic and pragmatic about the importance and access toclean power than back in 2014. Participants in the original survey projected22% of data center power would come from solar and an additional 12% from windby 2025. Thats a little more than one-third of data center power from thesetwo renewable sources, which seemed like an unrealistic projection at the time.

This years numbers for solar and wind (13% and 8% respectively) seem more realistic. However, importantly for Nordics countries with an abundance of hydropower, participants in this years survey expect hydro to be the largest energy source for data centers in 2025.

The data center 2025 research, also looked at one of theother big drivers for building capacity in the Nordics: access to efficientcooling.

According to the 2025 survey, around 42% of respondentsexpect future cooling requirements to be met by mechanical cooling systems. Liquidcooling and outside air also saw growth from 20% in 2014 to 22% in 2019, likelydriven by the more extreme rack densities being observed today. This growth inthe use of outside air obviously benefits temperate locations like the Nordics.

In summary, if the last ten years have been about simplykeeping up with data center demand, the next ten years will be about addingpurposeful capacity in the most efficient, sustainable and cost-effective way:the right data center type, thermal and power equipment, and location for theright workloads.

If the past is anything to go by, the Nordics will have an important role to play in that future.

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Artificial intelligence and machine learning for data centres and edge computing to feature at Datacloud Congress 2020 in Monaco - Data Economy