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Edge computing will grow but term is still confusing • The Register

Worldwide spending on edge computing is expected to see double-digit growth this year, according to new figures from analyst IDC.

It also predicted investments in edge will reach $176bn in 2022, an increase of 14.8 per cent over last year.

“Edge computing continues to gain momentum as digital-first organisations seek to innovate outside of the data centre,” IDC research vice president Dave McCarthy said in a statement, adding that the diverse needs of edge deployments have created a market opportunity for technology suppliers, increasingly through partnerships and alliances.

A great deal has been written about edge computing over the past several years, and yet it remains an area of technology that can be hard to define, as The Register has previously pointed out.

This has not stopped industry from trying to market edge solutions, so perhaps it is instructive to see what the industry currently thinks edge computing is all about.

IDC claimed to have identified more than 150 use cases for edge computing across various industries and domains, but says that the two edge use cases that will see the largest investments in 2022 are content delivery networks and virtual network functions.

In the enterprise space, the use cases IDC sees getting the largest investments in 2022 include manufacturing operations, production asset management, smart grids, freight monitoring, and intelligent transportation systems.

Process of elimination

The concept of edge computing is deceptively simple: put the processing where the data is being generated, rather than streaming it all back to a remote data centre, with the latency (and network costs) that inevitably incurs.

Step beyond that, and edge computing has such a diverse array of potential use cases that they often have little else in common, and thus building up a standard model or platform for “edge computing” remains elusive.

Meanwhile, one of the growing trends is for edge computing to be almost synonymous with AI, often because an application may call for a rapid or real-time response. Naturally, this model of edge computing is championed by Nvidia, which manufactures the GPUs that have become the accelerator of choice for many AI applications.

The GPU-flinger’s view of edge computing is actually quite pragmatic: it is the practice of moving compute power physically closer to where data is generated. The firm contrasts it with cloud, stating that edge computing reduces the need for large amounts of data to travel among servers, the cloud and devices or edge locations to get processed, which is particularly important for modern applications such as data science and AI.

Nvidia has its EGX platform designed especially for edge applications where data science and machine learning play a big part. This basically sees its GPUs married with Nvidia-certified systems hardware, operating a stack based on its CUDA framework and Kubernetes. In other words, it’s up to someone else to put it all together for you, Nvidia just provides the bits and pieces.

One firm that is getting more directly involved is Lenovo, which launched a new edge system, the ThinkEdge SE450, in December 2021. This is a compact ruggedised 2U server based on an Intel Xeon Platinum processor. It is also intended for applications involving AI and analytics with the ability to fit up to 4 GPUs.

At the launch, Lenovo revealed it is working with Barcelona City Council and local universities on projects that use its technology in “Smart City” style applications, using hardware such as the SE450 from its ThinkEdge series deployed in on-street cabinets dotted around the city. One application involves traffic management, analysing video feeds from cameras to detect if an accident has occurred and alerting the authorities.

One notable aspect of the ThinkEdge SE450 is its XClarity Controller, an embedded management engine that allows the system to be reached via a wired or wireless network connection for admin purposes, rather than having an engineer visit the site to perform maintenance. Managing edge systems is considered one of the major challenges of edge deployments, with kit distributed in remote locations rather than clustered together in a data centre.

Dell has similar systems, and also similar management features with the iDRAC9 management controller inside its servers. The firm outlined its view of the edge last year, in a blog by Alison Biers, director for Global Edge Solutions Marketing.

Biers said that Dell defines the edge as “where data is acted on near the point of creation to create immediate, essential value”, but goes on to add that delivering value at the edge requires the ability to consolidate and simplify IT and OT (operational technology). OT refers to systems used to monitor and control physical infrastructure, such as in building automation applications.

As well as ruggedised laptops, PowerEdge servers and its specialised Edge Gateway nodes, Dell also has the VxRail satellite node, which it introduced last year. As The Register noted at the time, this is a single-node version of the company’s hyperconverged platform which seems to be designed to allow a VMware environment to be operated in an edge scenario, but without the redundancy usually offered by a HCI cluster.

Perhaps the main issue with edge computing is that it is really a bunch of diverse applications that have been lumped together into one category, simply because they operate outside the bounds of the traditional data centre.

However you choose to define it, it looks like it isn’t going away. In Red Hat’s 2022 Global Tech Outlook report, edge computing was listed among the emerging technology workloads that organisations are most likely to consider over the coming year.

In fact, if you consider edge and IoT to overlap somewhat, the two combined were the leading category, with 61 per cent of respondents saying they were considering one or both.

Red Hat itself defines edge computing as a distributed computing model in which data is captured, stored, processed and analysed at or near the physical location where it is created. The firm says that it views it as “an opportunity to extend the open hybrid cloud all the way to the data sources and end users.”

This view that the edge is largely an extension of the cloud or the corporate data centre is shared by many vendors and analysts, with another recent report from IDC emphasising the need to find the appropriate location for workloads. Because workloads can reside across a continuum of core, edge, and endpoint locations, edge computing requires a significant amount of coordination among technology and service providers, it says.

IDC believes that the most significant edge workload opportunity is streamlining business intelligence and analytics, but perhaps surprisingly, does not see business application workloads as critical to the development of any major enterprise edge use cases.

“As edge technology continues to expand in usage in a variety of workplace environments, we are seeing growing interest in expected concurrent workload growth in areas such as business intelligence and analytics, AI/ML-related workloads, and content workloads,” IDC senior research analyst Max Pepper said in a statement announcing the report.

However, he added that the rapid deployment of edge computing is significantly shaping workload evolution.

Maybe the real lesson of edge computing is that an edge deployment will be intended to deliver a specific solution, and that this may demand specific hardware, software, and connectivity to meet those requirements, rather than just an off-the-shelf product.

In this case, the real opportunities for edge computing could lie with the systems integrators, which have the relevant skills to pull together a solution from various component parts and provide services to support customers in operating it.

This has been noted by edge vendor Stratus Solutions, which stated in a recent blog that the skillset of systems integrator engineers has never been in greater demand, and that they are extremely well positioned to benefit from the era of change.

Perhaps for this reason, IDC predicts that spending on professional and provisioned services will grow at a CAGR of 19.6 percent over the next five years. By 2025, it believes services will account for nearly 50 percent of all edge spending, led by investments in connectivity and edge-related infrastructure, platform, and software-as-a-service spending. ®

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Healthcare And Digital Upskilling

HeathTech & MedTech

According to EIT Health’s Elaine Murray and Sneha Saloni, it’s time to embrace digital upskilling within the healthcare industry

European Commission president, Ursula von der Leyen, announced last year that 2023 would be the ‘European Year of Skills’ with the objective of “a Europe fit for the digital age”. It will promote a mindset of reskilling and upskilling, helping people develop the right skills for the most in-demand jobs.

So, what does this mean for the healthcare sector? The European Health Parliament previously stated that, “digital technology is an inevitable part of the future of European healthcare” and called for upskilling healthcare workers.

Digital technologies such as AI, telemedicine and robotics, present huge potential for the way healthcare can be delivered, by maximising the reach and impact of various health services.

Preference is slowly shifting from brick and mortar to virtual healthcare and hence, many in the health sector are starting to reimagine and embrace digital to maximise efficiency and efficacy.

The digital skills gap

Healthcare professions make up approximately 10pc of the workforce in Europe, however estimates forecast that there is a shortage of approximately 1m health workers (600,000 in nursing, 230,000 physicians). Data demonstrates that healthcare companies are not visible among the most attractive employers in the eyes of talent.

Couple that with a 2020 report by the European Commission which stated that “shortages of software skills are now omnipresent” across Europe. The pandemic has not only boosted demand for tech-enabled healthcare services, with 90pc of all jobs in health soon to require an element of digital skills, but it has also widened the skill gap, placing stress on existing healthcare systems.

That means the industry is facing challenges in both recruiting into the sector and equipping the staff it does have with the digital skills they need. Many are either resistant or not well informed about new digital tools and systems. Lack of information and training among clinical and support staff acts as a deterrent to improving efficacy in patient care outcomes.

We therefore find ourselves at a critical juncture. Digital transformation in healthcare means increasing pressure on the existing system to perform, while sustaining and acknowledging the widening skills gap. Adequate investment in the workforce’s digital skills and digital literacy is now crucial.

Empowering healthcare professionals through digital upskilling

EIT Health, Europe’s largest health innovation network, is working to combat the talent shortage in the healthcare industry through its WorkInHealth Foundation. This aims to promote healthcare as a sector in which talent can thrive in Europe, particularly in the areas of digital, commercial, and innovation. EIT Health’s pan-European network links industry and academia which means it can tap into both recruiters and candidates, matching talent across the sector.

For those on the frontline, it can be difficult to stay abreast of so many fast-changing technologies entering the market. Whether it is a hospital administrator seeking to become proficient at using chatbots, cleaning staff adopting autonomous disinfection software, or a physician showing a patient how to use a medical device remotely, technology is integrated at every level of health service delivery.

A holistic approach needs to be adopted for upskilling by creating regular training opportunities for healthcare workers, senior executives and support staff so they can develop the digital expertise they need to carry out their roles efficiently and effectively.

There is also opportunity for institutions to shift from traditional training frameworks to digital alternatives. For example, training programmes to understand the integration of AI, data management, analytics and machine learning into existing infrastructure.

Initiatives such as the HSE’s Spark Innovation Programme create regular knowledge-building opportunities for healthcare staff in areas such as AI, design thinking, and innovation.

The Healthcare Transformation Academy, coordinated by EIT Health and organisations from the European University Hospital Alliance, offers high-quality and affordable on-demand courses in digital transformation, innovation management, high-value care and leadership for healthcare professionals to upskill.

The WorkInHealth Foundation also aims to support in upskilling and reskilling, increasing the volume of talent in the areas with greatest demand and boosting competitiveness of the European health industry. The initiative is in full alignment with the ambitions of the European Innovation Agenda as well as the EU Pact for Skills.

The European Year of Skills 2023 will help the healthcare sector navigate its digital transformation journey by address skills shortages in the EU, promoting a mindset of upskilling, which can ultimately improve patient care and increase reach in healthcare accessibility.


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How Entrepreneurial Mindset Is Necessary For Startup Triumph

Entrepreneurial Mindset & Startup Triumph

The Voice Of EU | In today’s dynamic world of startups, achieving exceptional growth isn’t a one-shot endeavor. It demands more than a stroke of luck or a hidden formula; it requires an unwavering entrepreneurial mindset, a steadfast commitment, and consistent, sustained effort.

How Entrepreneurial Mindset Is Necessary For Startup Triumph

Picture Credits: PS Vault

In the subsequent sections, I’ll dissect five crucial factors to high-performance growth psychology that can steer your startup towards unprecedented success.

1. The Primacy of Communication

In the quest for growth, it’s commonplace for companies to prioritize feature development over precise language. Yet, this approach is fundamentally misguided. Language should precede all else.

The words you choose to articulate your product and company not only define your identity but also establish user expectations. Your choice of language wields significant influence, shaping how users perceive and engage with your offering. For example, a ridesharing service becomes exponentially more appealing when it promises a ride in four minutes or less.

User-Centric Empathy

Successful Founders distinguish themselves by their ability to think beyond their product and focus on the users. It’s imperative to understand how users think and feel, considering the intricate web of their lives.

To truly stand out, you must ask, “What does my product mean to them, and how does it fit into their world?” Behind every thriving tech company lies a profound insight into human psychology, a key that resonates with users’ needs and desires.

Perpetual Motion

In a landscape dominated by industry giants, speed emerges as your greatest ally. Much like the ancient shrew that thrived through ceaseless motion, startups must embrace a similar philosophy, “be creative, be dynamic.”.

To navigate the whirlwind of rapid changes and outmaneuver larger competitors, you must be in perpetual motion. Swift experimentation, rapid iteration, and an unwavering forward momentum are the cornerstones of sustained growth.

The Embrace of Data

Commitment to measurement is the engine driving growth. Being truly data-driven is not merely a buzzword, but a fundamental philosophy. Devoting substantial engineering resources to measurement, up to half of your total, demonstrates a genuine love for data. It should be an integral part of your company culture, displayed prominently for all to see. Your daily stats should be a source of pride and a testament to your dedication to growth.

Resilience in the Face of Setbacks

Failure is a constant companion on the path to growth. Embracing a mindset that can endure these setbacks is crucial. Most initiatives will yield negative outcomes, and being able to move forward despite this is paramount.

It’s a psychology of resilience, encapsulated in the saying, ‘Success is going from failure to failure with no loss of enthusiasm‘. This grit and determination are the keys to achieving substantial growth.

Implementing Growth Psychology

To instill these growth-oriented mindsets in your team, consider the following steps:

1. Teach the mentality, particularly the willingness to endure repeated small failures.

2. Clarify that every member is directly responsible for growth, regardless of their official role.

3. Provide your team with the authority to drive product changes and allocate resources for growth.

4. Encourage your team to be more aggressive in pushing growth boundaries.

5. Keep taking big swings and be open to creative, high-risk strategies.

Ultimately, growth is a collective effort, but it hinges on the psychology of the CEO. Founders shape their startups through consistent actions and decisions.

Cultivating the right growth psychology can be the difference between sluggish progress and exponential success. It empowers your company with data-driven visibility, constant momentum, and the audacity to aim for 1000% growth.

If you’re in the latter camp, reach out to us to explore further opportunities for growth.


We Can’t Thank You Enough For Your Support!

— By Raza Qadri | Business, Science & Technology Contributor “The Voice Of EU

— For more information: Info@VoiceOfEU.com

— Anonymous news submissions: Press@VoiceOfEU.com


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4 Ways AI Is Transforming Social Media Marketing

Rebecca Barnatt-Smith explains how marketers and content creators can use AI-powered predicative analytics, content personalisation and scheduling tools to create successful social media campaigns.

Is artificial intelligence (AI) the next big thing for social media marketers?

With over 4.26bn social media users to serve, AI is set to transform targeting and improve content personalisation for a more focused marketing future.

AI is not a new phenomenon in the marketing world. When surveyed, over 56pc of chief marketing officers (CMOs) said they use automated assistants for content personalisation and tracking consumer insights. AI-driven social strategies are just the next step in a fast-approaching digital future of campaigning.

However, could a push for AI-infused social campaigns pose ethical concerns for future marketers? From breaching consumer privacy to decision system bias, with great technology comes great responsibility.

Here we look at AI’s impact on social media marketing and discuss some of the best AI-infused platforms that are tipped to lead social strategies in 2023.

How can AI improve your social media?

Using AI, you can quickly segment large demographics into targeted groups, track viral trends and schedule personalised content responses in seconds.

If you want to compete against commerce giants and industry leaders, your social content should be consistent, compelling and customised to each and every consumer. Here are some insights into how AI can help.

Content personalisation

In 2023, 73pc of shoppers expect brands to offer them a personalised experience and content that speaks directly to their values. AI can enhance a brand’s personalisation potential in a number of ways.

Automatically harvesting behavioural and historical consumer data, AI-generated platforms can quickly learn about a user’s interests and predict what products or services they’d be most likely to interact with, resulting in a hyper-individualised experience that can boost engagement and increase the chances of conversion.

However, with 69pc of consumers now concerned about how their data is collected and used on mobile apps, it’s important to use content personalisation tools with caution.

“As consumers continue to learn and become more informed about their data rights and how their data is currently used, I expect we’ll see more and more calls from consumers to have their data protected,” claims Swish Goswami, CEO of browser extension platform Surf.

The key here is to keep your consumers in the loop. Give your followers a chance to choose what they share, and make sure the data you collect is transparent. Personalised ads, posts and targeting is a business game changer, as long as you have consent.

Automated content posting

Creating content for your brand is the driving force behind audience engagement.

While experts recommend that brands upload social media content daily, this process can be time-consuming. Using AI-driven social media tools, marketers can feel the pressure drain away, as automated assistants not only create original content formats but automatically schedule them too.

For example, AI-infused content planner Sprout Social can generate personalised tweets that reply to fans and followers in seconds. Instead of physically manning social channels and checking for replies, Sprout Social monitors a brand’s comment section before analysing the tone and sentiment of a reply. Sprout can then suggest an auto-response that aims to carry on the conversation between the brand and the consumer.

While automatic replies can pose ethical questions about a brand’s true identity, Sprout Social ensures that before an automatic reply is posted, the social media manager is able to review and edit the content. This guarantees that the brand’s voice still has a human tone when connecting with its audience.

Hubspot is also a nifty tool to have under your belt, especially if you’re struggling to develop new content ideas. By simply pasting a content link into Hubspot’s content generation feature, it uses AI to quickly analyse the metadata and create an original social post.

Social media advertising

Social platforms are the perfect vessels for advertising success. Whether you choose TikTok or Instagram, with the ability to post a pop-up on a user’s scroll-down feed, or a sponsored TikTok that blends seamlessly into a For You Page, social channels allow for a more organic future of ad placement.

However, with so many brands utilising social media, it can be hard to make your ad stand out from the crowd. Your ads must be full of compelling captions, quick links to your online store and contain a personalised hook for your target consumer.

Using AI, brands can optimise their ad performance on social channels. With the ability to analyse historic campaigns and current trends among industry leaders, AI-driven ad tools such as Sprinklr can make recommendations for smarter campaigns that drive better results.

Also, AI-infused ad strategies are more likely to be personalised to each user’s feed. AI tools like Phrase can generate customisable ad phrasing that adapts to target individual customers. This is a great way to ensure your ad captions remain fluid and speak directly to a diverse set of leads.

Predictive analytics

While it’s easier than ever to track social media performance, acting on your results can be tricky. AI-generated monitoring tools utilise the data harvested on content engagement, clicks and consumers, and turn these insights into predictions for new campaigns, content formats and new target groups to work on.

The key here is to take these predictions and turn them into content campaigns that frame the values of your brand. It’s also important to do your own research before jumping into an AI-generated content campaign, as just like humans, AI can have a decision system bias.

“AI is fallible and in a perfect world should be used critically, responsibly and democratically,” says Annie Brown, founder of the creative sharing platform Lips. “AI is only as fair and accurate as the algorithm, and the algorithm is only as fair or accurate as the human-generated information it gathers.”

For example, if the only data your AI tool collects is from a specific consumer group, it’s likely to inherit the same biases. Therefore, it’s important to perform your own content research if you want your brand voice to remain objective on social media.

However, with more data to inform their strategy, brands that use AI to influence their social campaigns are more likely to see higher conversion payoffs.

As social platforms continue to become more visual, AI can also enhance video and image analysis. For example, AI algorithms can now identify certain aspects of Instagram images and TikTok videos, making it easier to gather more data on a user’s interests and behaviours.

Visual analytics could help a brand improve its content styles as AI tools learn more about audience preferences and the formats going viral.

Could AI take social media marketing to the next level?

AI can enhance the experience a consumer has with a brand on social media. With predictive analytics at play, the content targeted users receive is more likely to speak directly to their values.

While there are still ethical concerns surrounding an AI-infused future of campaigning, there’s hope on the horizon for data-sharing transparency and the impact of algorithmic biases as both consumers and marketers take control of how data is gathered and shared.

As machine learning gets even smarter, the possibilities are endless for brands that want to get close to their leads. From automated responses to automatic content creation, the future of social media marketing is AI-driven.

By Rebecca Barnatt-Smith

Rebecca Barnatt-Smith is a freelance content writer and multi-media marketing executive at Solvid Digital, specialising in social media trends and widespread digitalisation in the marketing sector.


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