Quantum computing is emerging as a groundbreaking force with the potential to reshape industries and enhance national security with unparalleled speed and precision. Governments and technology providers worldwide are heavily investing in this transformative technology, which promises significant advancements in areas such as cryptography, drug development, AI, and finance. Countries like Australia, Singapore, Taiwan, Qatar, and the UK are investing heavily in quantum research, backed by tech giants like Nvidia, IBM, and Google.
Ecosystm research finds that nearly 30% of enterprises are expecting to use quantum computing in the next 5 years.
Beyond Bits: Exploring the Potential of Quantum Computers
We need quantum computers because they have the potential to solve certain problems that are impossible (or impractical) for classical computers. Last year, Google led a study revealing that its quantum processor can complete a task in 6.18 seconds that would take a traditional supercomputer 47 years.
Here are a few reasons why quantum computing is exciting:
Unleashing the power of qubits. While classical computers use bits that can be either 0 or 1, quantum computers use qubits, which can exist in both states simultaneously (a state called superposition). This allows them to explore multiple possibilities simultaneously, making them significantly faster for specific tasks.
Tackling complex problems. Problems like simulating molecules or breaking complex encryption codes involve massive calculations. Quantum computers, with their unique properties, can manage these complexities more efficiently.
Revolutionising specific fields. Quantum computing has the potential to transform areas such as materials science, drug discovery, AI, and financial modelling. By simulating complex systems and processes, they could lead to breakthroughs in various sectors.
Quantum computers will not replace traditional computers entirely, but rather function as powerful tools for specific tasks beyond the reach of classical machines. Let’s look at cybersecurity as an example.
Twenty years ago, hacking was a basic task. Imagine a time before social media, when a simple computer and basic technical know-how were enough to breach a network. The stakes were low, the landscape uncomplicated. But technology, like threats, has evolved. Today’s hackers use sophisticated techniques, employing strategies like “harvest now, decrypt later” – stealing data today to decrypt later using more powerful machines. This is where quantum computing enters the scene, posing a significant threat to current encryption methods. In response, tech giants like Google, Apple, and Zoom are implementing quantum-resistant encryption into their software, safeguarding user data from potential future decryption attempts. Governments and telecommunication providers worldwide are boosting quantum encryption to tackle the potential security crisis.
The thrill of quantum computing lies in its infancy. Unforeseen applications, beyond our current imagination, could be unlocked as the technology matures.
Current Quantum Projects Focused on Security
First Scalable Network Secures Maritime Trade. The Netherlands is improving the resiliency of transport infrastructure in their own major international maritime hub, using quantum. The Port of Rotterdam Authority joined a collection of quantum technology firms to create a comprehensive cybersecurity ecosystem – the first of its kind globally. The port uses quantum technology to safeguard sensitive information, improving safety for the seagoing vessels carrying 470 million tonnes of cargo annually.
UK Integrates Quantum Navigation for Secure Air Travel. The UK is improving its digital transport infrastructure by integrating the first ever un-jammable aviation navigation system, powered by quantum software. This initiative was prompted by an incident where a government plane carrying the UK defence secretary had its GPS signal jammed close to Russian territory. This technology ensures safe and reliable navigation for aircraft, particularly in hostile environments. The UK government is investing USD 56 million into their quantum sector, aiming to become a quantum-enabled economy by 2033.
Governments Putting Faith in Quantum
Taiwan’s First Domestic 5-Qubit Computer. Taiwan is aiming to be a leader in quantum computing by building its first domestic machine by 2027. This initiative is part of a larger USD 259 million, five-year plan for quantum technology, and has a multi-pronged approach including building the actual quantum computer hardware; developing solutions to secure data in a world with quantum computers (quantum cryptography); creating a strong supply chain for quantum computing components within Taiwan; and collaborating with international partners to develop testing platforms and expertise.
Singapore Explores Real-World Applications. The Singaporean government has pledged USD 518 million to their National Quantum Strategy (NQS). This investment will provide the necessary resources to explore real-time applications of quantum technology in healthcare and technology. Simultaneously, they launched the National Quantum Processor Initiative (NQPI) to develop quantum sensors that will aid in research. Singapore aims to lead the world in quantum tech for investment portfolios, cryptography, and drug discovery.
Australia Aiming for World’s First Utility-Scale Machine. Backed by a USD 620 million investment from the Australian and Queensland governments, PsiQuantum aims to build a fault-tolerant computer that can solve previously challenging problems in fields like renewable energy, healthcare, and transportation. PsiQuantum’s innovative “fusion-based architecture” tackles scaling challenges by using millions of light-based qubits, paving the way for a new era of computational power and potentially sparking the next industrial revolution. This project positions Australia as a global leader in harnessing the immense potential of quantum computing.
Tech Companies Making the Quantum Leap
IBM Enhances Quantum Performance. IBM’s latest quantum computing platform, Qiskit 1.0, has worked on features that enhance performance, stability, and reliability. The updated open-source SDK aims to facilitate accessible quantum programming and accelerate processing times. Qiskit 1.0 uses optimised circuits to create and manage the interplay between classical and quantum computing. IBM is even collaborating with Japan’s AIST to develop a 10,000-qubit quantum computer by 2029, which is 75 times more powerful than current systems.
Microsoft and Quantinuum Achieve Reliable Logical Qubits. This significant milestone is said to mark a new era of dependable quantum technology, dramatically reducing errors and enhancing the precision of quantum computations. They have demonstrated an 800x improvement in error rates, paving the way for hybrid supercomputing systems that combine AI, high-performance computing (HPCs), and quantum capabilities to tackle scientific problems, with new capabilities becoming available to Azure Quantum Elements customers in the coming months.
Quantum Cloud Services for Enterprise. Major tech players QMware, Nvidia, and Oracle are teaming up to create hybrid quantum computing service for businesses. Combining classical and quantum computing, the project aims to crunch complex problems in AI, machine learning, and optimisation – all in the cloud.
Building Towards a Quantum Future
In the short term, using HPCs with quantum algorithms can already provide noticeable speed improvements over traditional methods. Hybrid approaches, where HPCs and quantum computers work together, could lead to significant gains in speed and efficiency, potentially ranging from 10x to 100x improvement.
Three strategies: quantum-inspired, hybrid, and full-scale quantum computing each offer distinct advantages.
While quantum-inspired computing leverages quantum algorithms to run on classical systems, hybrid computing combines classical and quantum processors, optimising the strengths of both to take complex problems more efficiently. Intuitively, full-scale quantum computing represents the ultimate goal, where large, fault-tolerant quantum computers solve problems beyond the reach of current classical systems.
Looking further ahead, the development of large-scale quantum computers could revolutionise industries by solving problems far beyond the reach of classical computers, with potential speedups of 500x to 1000x.
As quantum technology progresses, different industries and applications will benefit from tailored approaches that best suit their unique needs.
Southeast Asia’s massive workforce – 3rd largest globally – faces a critical upskilling gap, especially with the rise of AI. While AI adoption promises a USD 1 trillion GDP boost by 2030, unlocking this potential requires a future-proof workforce equipped with AI expertise.
Governments and technology providers are joining forces to build strong AI ecosystems, accelerating R&D and nurturing homegrown talent. It’s a tight race, but with focused investments, Southeast Asia can bridge the digital gap and turn its AI aspirations into reality.
Read on to find out how countries like Singapore, Thailand, Vietnam, and The Philippines are implementing comprehensive strategies to build AI literacy and expertise among their populations.
Download ‘Upskilling for the Future: Building AI Capabilities in Southeast Asia’ as a PDF
Big Tech Invests in AI Workforce
Southeast Asia’s tech scene heats up as Big Tech giants scramble for dominance in emerging tech adoption.
Microsoft is partnering with governments, nonprofits, and corporations across Indonesia, Malaysia, the Philippines, Thailand, and Vietnam to equip 2.5M people with AI skills by 2025. Additionally, the organisation will also train 100,000 Filipino women in AI and cybersecurity.
Singapore sets ambitious goal to triple its AI workforce by 2028. To achieve this, AWS will train 5,000 individuals annually in AI skills over the next three years.
NVIDIA has partnered with FPT Software to build an AI factory, while also championing AI education through Vietnamese schools and universities. In Malaysia, they have launched an AI sandbox to nurture 100 AI companies targeting USD 209M by 2030.
Singapore Aims to be a Global AI Hub
Singapore is doubling down on upskilling, global leadership, and building an AI-ready nation.
Singapore has launched its second National AI Strategy (NAIS 2.0) to solidify its global AI leadership. The aim is to triple the AI talent pool to 15,000, establish AI Centres of Excellence, and accelerate public sector AI adoption. The strategy focuses on developing AI “peaks of excellence” and empowering people and businesses to use AI confidently.
In keeping with this vision, the country’s 2024 budget is set to train workers who are over 40 on in-demand skills to prepare the workforce for AI. The country will also invest USD 27M to build AI expertise, by offering 100 AI scholarships for students and attracting experts from all over the globe to collaborate with the country.
Thailand Aims for AI Independence
Thailand’s ‘Ignite Thailand’ 2030 vision focuses on boosting innovation, R&D, and the tech workforce.
Thailand is launching the second phase of its National AI Strategy, with a USD 42M budget to develop an AI workforce and create a Thai Large Language Model (ThaiLLM). The plan aims to train 30,000 workers in sectors like tourism and finance, reducing reliance on foreign AI.
The Thai government is partnering with Microsoft to build a new data centre in Thailand, offering AI training for over 100,000 individuals and supporting the growing developer community.
Building a Digital Vietnam
Vietnam focuses on AI education, policy, and empowering women in tech.
Vietnam’s National Digital Transformation Programme aims to create a digital society by 2030, focusing on integrating AI into education and workforce training. It supports AI research through universities and looks to address challenges like addressing skill gaps, building digital infrastructure, and establishing comprehensive policies.
The Vietnamese government and UNDP launched Empower Her Tech, a digital skills initiative for female entrepreneurs, offering 10 online sessions on GenAI and no-code website creation tools.
The Philippines Gears Up for AI
The country focuses on investment, public-private partnerships, and building a tech-ready workforce.
With its strong STEM education and programming skills, the Philippines is well-positioned for an AI-driven market, allocating USD 30M for AI research and development.
The Philippine government is partnering with entities like IBPAP, Google, AWS, and Microsoft to train thousands in AI skills by 2025, offering both training and hands-on experience with cutting-edge technologies.
The strategy also funds AI research projects and partners with universities to expand AI education. Companies like KMC Teams will help establish and manage offshore AI teams, providing infrastructure and support.
For many organisations migrating to cloud, the opportunity to run workloads from energy-efficient cloud data centres is a significant advantage. However, carbon emissions can vary from one country to another and if left unmonitored, will gradually increase over time as cloud use grows. This issue will become increasingly important as we move into the era of compute-intensive AI and the burden of cloud on natural resources will shift further into the spotlight.
The International Energy Agency (IEA) estimates that data centres are responsible for up to 1.5% of global electricity use and 1% of GHG emissions. Cloud providers have recognised this and are committed to change. Between 2025 and 2030, all hyperscalers – AWS, Azure, Google, and Oracle included – expect to power their global cloud operations entirely with renewable sources.
Chasing the Sun
Cloud providers are shifting their sights from simply matching electricity use with renewable power purchase agreements (PPA) to the more ambitious goal of operating 24/7 on carbon-free sources. A defining characteristic of renewables though is intermittency, with production levels fluctuating based on the availability of sunlight and wind. Leading cloud providers are using AI to dynamically distribute compute workloads throughout the day to regions with lower carbon intensity. Workloads that are processed with solar power during daylight can be shifted to nearby regions with abundant wind energy at night.
Addressing Water Scarcity
Many of the largest cloud data centres are situated in sunny locations to take advantage of solar power and proximity to population centres. Unfortunately, this often means that they are also in areas where water is scarce. While liquid-cooled facilities are energy efficient, local communities are concerned on the strain on water sources. Data centre operators are now committing to reduce consumption and restore water supplies. Simple measures, such as expanding humidity (below 20% RH) and temperature tolerances (above 30°C) in server rooms have helped companies like Meta to cut wastage. Similarly, Google has increased their reliance on non-potable sources, such as grey water and sea water.
From Waste to Worth
Data centre operators have identified innovative ways to reuse the excess heat generated by their computing equipment. Some have used it to heat adjacent swimming pools while others have warmed rooms that house vertical farms. Although these initiatives currently have little impact on the environmental impact of cloud, they suggest a future where waste is significantly reduced.
Greening the Grid
The giant facilities that cloud providers use to house their computing infrastructure are also set to change. Building materials and construction account for an astonishing 11% of global carbon emissions. The use of recycled materials in concrete and investing in greener methods of manufacturing steel are approaches the construction industry are attempting to lessen their impact. Smaller data centres have been 3D printed to accelerate construction and use recyclable printing concrete. While this approach may not be suitable for hyperscale facilities, it holds potential for smaller edge locations.
Rethinking Hardware Management
Cloud providers rely on their scale to provide fast, resilient, and cost-effective computing. In many cases, simply replacing malfunctioning or obsolete equipment would achieve these goals better than performing maintenance. However, the relentless growth of e-waste is putting pressure on cloud providers to participate in the circular economy. Microsoft, for example, has launched three Circular Centres to repurpose cloud equipment. During the pilot of their Amsterdam centre, it achieved 83% reuse and 17% recycling of critical parts. The lifecycle of equipment in the cloud is largely hidden but environmentally conscious users will start demanding greater transparency.
Recommendations
Organisations should be aware of their cloud-derived scope 3 emissions and consider broader environmental issues around water use and recycling. Here are the steps that can be taken immediately:
- Monitor GreenOps. Cloud providers are adding GreenOps tools, such as the AWS Customer Carbon Footprint Tool, to help organisations measure the environmental impact of their cloud operations. Understanding the relationship between cloud use and emissions is the first step towards sustainable cloud operations.
- Adopt Cloud FinOps for Quick ROI. Eliminating wasted cloud resources not only cuts costs but also reduces electricity-related emissions. Tools such as CloudVerse provide visibility into cloud spend, identifies unused instances, and helps to optimise cloud operations.
- Take a Holistic View. Cloud providers are being forced to improve transparency and reduce their environmental impact by their biggest customers. Getting educated on the actions that cloud partners are taking to minimise emissions, water use, and waste to landfill is crucial. In most cases, dedicated cloud providers should reduce waste rather than offset it.
- Enable Remote Workforce. Cloud-enabled security and networking solutions, such as SASE, allow employees to work securely from remote locations and reduce their transportation emissions. With a SASE deployed in the cloud, routine management tasks can be performed by IT remotely rather than at the branch, further reducing transportation emissions.
Google recently extended its Generative AI, Bard, to include coding in more than 20 programming languages, including C++, Go, Java, Javascript, and Python. The search giant has been eager to respond to last year’s launch of ChatGPT but as the trusted incumbent, it has naturally been hesitant to move too quickly. The tendency for large language models (LLMs) to produce controversial and erroneous outputs has the potential to tarnish established brands. Google Bard was released in March in the US and the UK as an LLM but lacked the coding ability of OpenAI’s ChatGPT and Microsoft’s Bing Chat.
Bard’s new features include code generation, optimisation, debugging, and explanation. Using natural language processing (NLP), users can explain their requirements to the AI and ask it to generate code that can then be exported to an integrated development environment (IDE) or executed directly in the browser with Google Colab. Similarly, users can request Bard to debug already existing code, explain code snippets, or optimise code to improve performance.
Google continues to refer to Bard as an experiment and highlights that as is the case with generated text, code produced by the AI may not function as expected. Regardless, the new functionality will be useful for both beginner and experienced developers. Those learning to code can use Generative AI to debug and explain their mistakes or write simple programs. More experienced developers can use the tool to perform lower-value work, such as commenting on code, or scaffolding to identify potential problems.
GitHub Copilot X to Face Competition
While the ability for Bard, Bing, and ChatGPT to generate code is one of their most important use cases, developers are now demanding AI directly in their IDEs.
In March, Microsoft made one of its most significant announcements of the year when it demonstrated GitHub Copilot X, which embeds GPT-4 in the development environment. Earlier this year, Microsoft invested $10 billion into OpenAI to add to the $1 billion from 2019, cementing the partnership between the two AI heavyweights. Among other benefits, this agreement makes Azure the exclusive cloud provider to OpenAI and provides Microsoft with the opportunity to enhance its software with AI co-pilots.
Currently, under technical preview, when Copilot X eventually launches, it will integrate into Visual Studio — Microsoft’s IDE. Presented as a sidebar or chat directly in the IDE, Copilot X will be able to generate, explain, and comment on code, debug, write unit tests, and identify vulnerabilities. The “Hey, GitHub” functionality will allow users to chat using voice, suitable for mobile users or more natural interaction on a desktop.
Not to be outdone by its cloud rivals, in April, AWS announced the general availability of what it describes as a real-time AI coding companion. Amazon CodeWhisperer, integrates with a range of IDEs, namely Visual Studio Code, IntelliJ IDEA, CLion, GoLand, WebStorm, Rider, PhpStorm, PyCharm, RubyMine, and DataGrip, or natively in AWS Cloud9 and AWS Lambda console. While the preview worked for Python, Java, JavaScript, TypeScript, and C#, the general release extends support for most languages. Amazon’s key differentiation is that it is available for free to individual users, while GitHub Copilot is currently subscription-based with exceptions only for teachers, students, and maintainers of open-source projects.
The Next Step: Generative AI in Security
The next battleground for Generative AI will be assisting overworked security analysts. Currently, some of the greatest challenges that Security Operations Centres (SOCs) face are being understaffed and overwhelmed with the number of alerts. Security vendors, such as IBM and Securonix, have already deployed automation to reduce alert noise and help analysts prioritise tasks to avoid responding to false threats.
Google recently introduced Sec-PaLM and Microsoft announced Security Copilot, bringing the power of Generative AI to the SOC. These tools will help analysts interact conversationally with their threat management systems and will explain alerts in natural language. How effective these tools will be is yet to be seen, considering hallucinations in security is far riskier than writing an essay with ChatGPT.
The Future of AI Code Generators
Although GitHub Copilot and Amazon CodeWhisperer had already launched with limited feature sets, it was the release of ChatGPT last year that ushered in a new era in AI code generation. There is now a race between the cloud hyperscalers to win over developers and to provide AI that supports other functions, such as security.
Despite fears that AI will replace humans, in their current state it is more likely that they will be used as tools to augment developers. Although AI and automated testing reduce the burden on the already stretched workforce, humans will continue to be in demand to ensure code is secure and satisfies requirements. A likely scenario is that with coding becoming simpler, rather than the number of developers shrinking, the volume and quality of code written will increase. AI will generate a new wave of citizen developers able to work on projects that would previously have been impossible to start. This may, in turn, increase demand for developers to build on these proofs-of-concept.
How the Generative AI landscape evolves over the next year will be interesting. In a recent interview, OpenAI’s founder, Sam Altman, explained that the non-profit model it initially pursued is not feasible, necessitating the launch of a capped-for-profit subsidiary. The company retains its values, however, focusing on advancing AI responsibly and transparently with public consultation. The appearance of Microsoft, Google, and AWS will undoubtedly change the market dynamics and may force OpenAI to at least reconsider its approach once again.
Innovation and collaboration are the cornerstones of FinTech success stories. Successful FinTechs have identified market gaps and designed innovative solutions to address these gaps. They have also built an ecosystem of partners – such as other FinTechs, large corporates and financial services organisations – to deliver better customer experiences, create process efficiencies and make compliance easier.
As FinTechs have become mainstream over the years the innovations and the collaborations continue to make technology and business headlines.
Here are some recent trends:
- The Growth of Cross-border Finance. Globalisation and the rise of eCommerce have created a truly global marketplace – and financial agencies such as the MAS and those in the EU are responding to the need.
- Transparency through Smart Contracts. As businesses and platforms scale applications and capabilities through global partnerships, there is a need for trusted, transparent transactions. Symbiont‘s partnership with Swift and BNB Chain‘s tie-up with Google Cloud are some recent examples.
- Evolution of Digital Payments. Digital payments have come a long way from the early days of online banking services and is now set to move beyond digital wallets such as the Open Finance Association and EU initiatives to interlink domestic CBDCs.
- Banks Continue to Innovate. They are responding to market demands and focus on providing their customers with easy, secure, and enhanced experiences. NAB is working on digital identity to reduce fraud, while Standard Chartered Bank is collaborating with Bukalapak to introduce new digital services.
- The Emergence of Embedded Finance. In the future, we will see more instances of embedded financial services within consumer products and services that allows seamless financial transactions throughout customer journeys. LG Electronics‘ new NFT offering is a clear instance.
Read below to find out more.
Download The Future of Finance: FinTech Innovations & Collaborations as a PDF
Last week, Kyndryl became a Premier Global Alliance Partner for AWS. This follows other recent similar partnerships for Kyndryl with Google and Microsoft. This now gives Kyndryl premier or similar partner status at the big three hyperscalers.
The Partnership
This new partnership was essential for Kyndryl to provide legitimacy to their independent reputation and their global presence. And in many respects, it is a partnership that AWS needs as much as Kyndryl does. As one of the largest global managed services providers, Kyndryl manages a huge amount of infrastructure and thousands of applications. Today, most of these applications sit outside public cloud environments, but at some stage in the future, many of these applications will move to the public cloud. AWS has positioned itself to benefit from this transition – as Kyndryl will be advising clients on which cloud environment best suits their needs, and in many cases Kyndryl will also be running the application migration and managing the application when it resides in the cloud. To that end, the further investment in developing an accelerator for VMware Cloud on AWS will also help to differentiate Kyndryl on AWS. With a high proportion of Kyndryl customers running VMware, this capability will help VMware users to migrate these workloads to the cloud and run core businesses services on AWS.
The Future
Beyond the typical partnership activities, Kyndryl will build out its own internal infrastructure in the cloud, leveraging AWS as its preferred cloud provider. This experience will mean that Kyndryl “drinks its own champagne” – many other managed services providers have not yet taken the majority of their infrastructure to the cloud, so this experience will help to set Kyndryl apart from their competitors, along with providing deep learning and best practices.
By the end of 2022, Kyndryl expects to have trained more than 10,000 professionals on AWS. Assuming the company hits these targets, they will be one of AWS’s largest partners. However, experience trumps training, and their relatively recent entry into the broader cloud ecosystem space (after coming out from under IBM’s wing at the end of 2021) means they have some way to go to have the depth and breadth of experience that other Premier Alliance Partners have today.
Ecosystm Opinion
In my recent interactions with Kyndryl, what sets them apart is the fact that they are completely customer-focused. They start with a client problem and find the best solution for that problem. Yes – some of the “best solutions” will be partner specific (such as SAP on Azure, VMware on AWS), but they aren’t pushing every customer down a specific path. They are not just an AWS partner – where every solution to every problem starts and ends with AWS. The importance of this new partnership is it expands the capabilities of Kyndryl and hence expands the possibilities and opportunities for Kyndryl clients to benefit from the best solutions in the market – regardless of whether they are on-premises or in one of the big three hyperscalers.
COP26 has firmly put environmental consciousness as a leading global priority. While we have made progress in the last 30 odd years since climate change began to be considered as a reality, a lot needs to be done.
No longer is it enough for only governments to lead on green initiatives. Now is the time for non-profit organisations, investors, businesses – corporate and SMEs – and consumers to come together to ensure we leave a safer planet for our children.
February saw examples of how technology providers and large corporates are delivering on their environmental consciousness and implementing meaningful change.
Here are some announcements that show how tech providers and corporates are strengthening the Sustainability cause:
- IBM launches Sustainability Accelerator Program
- Microsoft boosts their Sustainability offerings by extending extend their EID tool for Microsoft 365
- Salesforce officially announce sustainability as a core company value
- Google enables Sustainable AIOps
- The Aviation industry (Southwest Airlines, ANA, Norwegian Air and Singapore Airlines) appears to be making a concerted effort to reduce carbon footprint.
Read on to find more.
Click here to download a copy of The Future of Sustainability as a PDF.
Since officially separating from IBM in November last year, Kyndryl has been busy cementing some heavyweight partnerships. The alliances with Microsoft, Google, and VMware demonstrate its intention to build hybrid cloud solutions with whoever it needs to, rather than favouring the Big Blue or Red Hat. The SAP tie-up hints at a future of migrating ERP workloads to the cloud and even an eye on moving up the application stack. Last week Kyndryl announced it is working with Nokia to provide private 5G and LTE networks to enable Industry 4.0 solutions. The first customer reference for the partnership is Dow, deploying both real-world and proof-of-concept applications for worker safety and collaboration and asset tracking.
The Partnership
Kyndryl has a competitive networking services unit, particularly in partnership with Cisco. Its focus has been on SD-WAN, campus networks, and network management as part of broader cloud services deals. This 5G partnership with Nokia is its first serious effort to work with one of the major carrier-grade vendors using cellular technology. It creates an opportunity for Kyndryl to position itself as a provider of services that underpin IoT and edge applications, rather than only cloud, which has until now been its main strength.
Prior to the Kyndryl announcement, Nokia was already developing private 5G solutions under the moniker Digital Automation Cloud (DAC). A key customer is Volkswagen, using the network to connect robots and wireless assembly tools. Over-the-air vehicle updates are also tested over the private network. Volkswagen operates in a dedicated 3.7-3.8 GHz band, which was allocated by the Federal Network Agency in Germany. This illustrates a third option for accessing spectrum, which will become an important consideration in private 5G rollouts.
Private 5G Use Cases
Private 5G has several benefits such as low latency, long-range, support for many users per access point, and provision for devices that are mobile due to handover. It is unlikely that it will completely replace other technologies, like wireless LAN, but it is very compelling for certain use cases.
Private 5G is useful on large sites, like mines, ports, farms, and warehouses where connected machines are moving about or some devices – like perimeter security cameras – are just out of reach. Utilities, like power, gas, and water, with infrastructure that needs to be monitored over long distances, will also start looking at it as a part of their predictive maintenance and resiliency systems. Low latency will become increasingly important as we see more and more customer-facing digital services delivered on-site and autonomous robots in the production environment.
Another major benefit of private 5G compared to operating on public service is that data can remain within the organisation’s own network for as long as possible, providing more security and control.
Private 5G Gaining Popularity
There has been a lot of activity over the last year in this space, with the hyperscalers, telecom providers and network equipment vendors developing private 5G offerings.
Last year, the AWS Private 5G was announced, a managed service that includes core network hardware, small-cell radio units, SIM cards, servers, and software. The service operates over a shared spectrum, like the Citizens Broadband Radio Service (CBRS) in the US, where the initial preview will be available. CBRS is considered a lightly licenced band. This builds on AWS’s private multi-access edge compute (MEC) solution, released in conjunction with Verizon to integrate AWS Outposts with private 5G operating in licenced spectrum. A customer reference highlighted was low latency, high throughput analysis of video feeds from manufacturing robots at Corning.
Similarly, Microsoft launched a private MEC offering last year, a cloud and software stack designed for operators, systems integrators, and ISVs to deploy private 5G solutions. The system is built up of components from Azure and its acquisition of Metaswitch. AT&T is an early partner bringing a solution to the market built on Microsoft’s technology and the operator’s licenced spectrum. Microsoft highlighted use cases such as asset tracking in logistics, factory operations in manufacturing, and experiments with AI-infused video analytics to improve worker safety.
The Future
Organisations are likely to begin testing private 5G this year for Industry 4.0 applications, either at single sites in the case of factories or in select geographic areas for Utilities. Early applications will mostly focus on simple connectivity for mobile machines or remote equipment. In the longer term, however, the benefits of private 5G will become more apparent as AI applications, such as video analysis and autonomous machines become more prevalent. This will require the full ecosystem of players, including telecom providers, network vendors, cloud hyperscalers, systems integrators, and IoT providers.
