Top 8 Technology Trends for 2020 and Beyond
2020 is just around the corner with new technologies and approaches that bring us ever closer to the 4th Industrial Revolution.
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2020 is just around the corner with new technologies and approaches that bring us ever closer to the 4th Industrial Revolution. The increasingly rapid pace at which technology is evolving today makes it extremely hard but crucial for companies to keep up with every change, every bit of progress in the digital world.
What was but a theory yesterday may as well become a standard tomorrow. From the exponential growth of the Internet of things, artificial intelligence, and immersive digital experiences to the future of data security, management, and storage, here are the eight most promising technologies you should keep a keen eye on in the next decade.
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While the adoption of cloud computing is growing exponentially — Google Cloud, AWS (Amazon Web Services), Microsoft Azure—showing a perfect fit for the needs of thousands of companies today, there are still many current and emerging technologies that require a different approach to information processing.
Internet-of-Things systems, industrial automation, augmented reality, and other promising technologies that rely on high-performance computing require a significantly lower latency to show their full potential than cloud computing can provide today. This raises an increased interest in edge computing and its distributed capabilities.
Edge computing is a distributed computing paradigm that can help IoT and the related tech bypass high latency of cloud computing by bringing data storage and processing closer to where it needs to happen—time-sensitive data computation occurs within the device itself while the rest is executed in the distributed cloud. Thus, the devices become small, local data centers capable of efficiently processing data in remote locations with limited or no connectivity to the cloud.
The idea of keeping traffic local and distributed helps companies to drastically improve response times, save bandwidth, as well as enable greater autonomy of their software and hardware solutions. One of the most successful examples of edge computing is Amazon’s PrimeAir and its package delivery drones.
Drones, industrial and social robots, autonomous vehicles, as well as various automated systems, all benefit from superior interconnectivity, infrastructure optimization, and lower bandwidth costs brought by edge computing. According to the report by Allied Market Research, the global edge computing market is expected to reach $16.55 billion by 2025 and create various new jobs, primarily for software engineers.
Artificial intelligence is a term used to describe a wide variety of technologies and computer systems built to simulate human intelligence processes, including learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. It has been one of the biggest trends in recent years and is likely to be one of the next great technological shifts.
While it’s not exactly a new trend, AI is something to keep an eye on considering its incredible transformative potential. The adoption has already begun across industries—from ubiquitous chatbots to complex predictive analytics tools—and the demand for AI-powered solutions is growing at a great pace. The statistic shows that the global AI software market will reach approximately 15 billion dollars in 2020 which means AI is becoming a lot more than just a trend.
Today AI-powered software is an integral component of digital transformation strategies of practically every company out there. Artificial intelligence, machine learning, and other cognitive tools drive automation across IT ecosystems. Organizations redesign their core systems, establish new business approaches, and reorganize their processes around AI solutions and their strongest cognitive possibilities: data-driven insights, data-informed decision making, and increased productivity.
Whereas large corporations and wealthy organizations do have the capacity to design and deploy their AI-powered systems, most SMEs would have to resort to different, less expensive approaches when embarking on their AI-fueled journeys. The most realistic options to consider in 2020 are AI-as-a-service and open-algorithm models.
Though still pretty pricey in terms of customization to the specific tasks an organization may require, the AI-as-a-service model will be an attainable option provided by the likes of Google, Amazon, IBM, and Microsoft. We can also expect a growing pool of startups and vendors providing both paid AI services and open-algorithm models tailored for specific business needs and use cases in the next 2-3 years.
Robotic Process Automation and Hyperautomation
Like Artificial Intelligence and Machine Learning, Robotic Process Automation (RPA) is meant to make our lives easier through digital transformation and automation of complex business processes — data processing, workflow optimization, supply chain management, and another complex, repetitive tasks that once required humans.
While automation has always been a hot topic for numerous employment disputes — recent Forrester Research report estimates that automation currently threatens about 9% of the global workforce — today merely 5% of jobs can be entirely automated. Over the next decade, the technology is more likely to alter existing jobs, making them easier to do through partial automation, and significantly increase the demand for business analysts, software architects, engineers, and other IT personnel.
The next step in automation will be combining RPA with the aforementioned AI, ML — as well as other automation tools, intelligent business management software, and process mining techniques—that allow us to automate processes and augment humans in even more impactful ways. This combination of technologies and processes is called hyper-automation.
The goal of hyper-automation is to understand the range of automation mechanisms that would enable machines to automate themselves with little to no external help from humans — discover, analyze, design, measure, monitor and reassess.
Soon, hyper-automation will be used by companies worldwide to create DTOs (digital twin of an organization), a dynamic, virtual model of an organization, its products, services, and processes which enable companies to analyze and experiment with real-time, continuous intelligence in a simulated environment. Such AI-fueled decision making will drive significant value and business opportunities for companies that adopt it the earliest in the next decade.
Extended reality (XR) is a term that refers to the three representative forms of immersive digital experiences provided by computer technology and wearables: virtual reality (VR), augmented reality (AR), and mixed reality (MR). VR is a full immersion into a digital environment where you interact with digital objects using special headsets with controllers or multi-projected environments.
AR provides an interactive experience by enhancing real-world objects with computer-generated perceptual information that you can interact with through smartphones, tablets, eyeglasses, and all kinds of other devices. Finally, MR pushes AR a step forward by merging real-world and virtual experiences where physical and digital objects co-exist and users can interact with digital objects placed in the real world and vice versa in real-time.
Even though XR technologies are mostly applied in entertainment and experiential marketing today, they are changing the way we perceive and interact with the real and digital world. In 2020 and forth, these technologies are expected to be widely implemented across numerous other domains like healthcare, education, and retail.
Extended reality will be effectively applied for training, simulation, manufacturing, prototyping, business communication, e-commerce, customer engagement, and many other kinds of interactions between humans, businesses, machines, and data.
Extensive capabilities of artificial intelligence, the Internet of things, robotics, edge computing, and extended reality in combination with human-centered design techniques open the way for a system called Intelligent Interface. One of the most common features of these human-computer interfaces is the ability to gather data about the user, predict what the user wants, and provide them with information or services more adequate to their needs.
The early birds of the intelligent-interfaces development are conversational technologies like virtual assistants and voice-enabled wearables that allow you to interact with your environment and the digital world hands-free. While we use these systems for giving simple commands to our smart homes and phones, businesses today successfully apply them in logistics, customer service, and field operations.
So far retail and marketing are showing the biggest interest in the development of intelligent interfaces to identify customers, analyze their looks, mood, and physical behavior, as well as track their digital habits to push real-time promotions, recommendations, and target ads.
Such significantly more intuitive and efficient interfaces will play a huge role in the Industry 4.0 transformation. Over the next decade, there will be major improvements in natural language processing, computer vision, facial recognition, eye tracking, emotion recognition, gesture control, and other related technologies that will drive the development of new, advanced intelligent interfaces for both private and business needs.
Intelligent interfaces will be able to understand customers at a deeper level, providing them with more personalized services and custom products. The convenience of intelligent interfaces and their cognitive capabilities will help companies enhance the individual productivity of every employee and increase the company’s overall operational efficiency.
We can also expect technologies like brain-controlled interfaces, muscle-computer interfaces, and spatial computing to rise in 2020, bringing us a whole lot of mind-blowing opportunities in years to come.
Distributed Ledger Technology
Blockchain, one of the most renowned distributed ledger technologies, has been a very controversial topic since back when Bitcoin, the first cryptocurrency in the world, began on its path. Today the technology continues to raise waves of heated discussions, mostly due to overhyped projects — related to blockchain-based cryptocurrencies — that failed miserably and thousands of scams that cost ill-informed investors their fortunes. Nevertheless, 2020 may yet be the year distributed ledger technology finally washes the dirt off of its reputation.
Today corporations around the world refuse to give up on DLTs’ transformational potential as a pragmatic solution to business problems across industries and use cases. DLTs have become their top-five strategic priority—IBM, Facebook, Microsoft, Alphabet, Samsung, Mastercard, Walmart, Oracle, Tencent—these and many more companies continue investing billions of dollars into the development of their cryptocurrencies, marketplaces, digital IDs, supply-chain management systems, and various other decentralized solutions.
Over the next decade, these decentralized peer-to-peer systems will have the capacity to reshape entire industries. DLT-based solutions have the potential to enable trust between companies and users, bring transparency to business operations, improve traceability of various assets, lower costs of transactions, eliminate borders for value exchange, and ensure security and immutability of private data.
Digital IDs, Data Security, and Privacy
As the World Economic Forum stated back in 2011, “Personal data is becoming a new economic ‘asset class’, a valuable resource for the 21st century that will touch all aspects of society.” From our hobbies to transaction history, more and more of our data ends up in the hands of large corporations like Facebook and Google.
They collect this data and use it for things like targeted advertising or even trade it with other companies which leads to disastrous cases of misuse like the Facebook–Cambridge Analytica data scandal. And unfortunately, there’s not much you can do today to protect your data except completely refusing the services of these companies or going full offline.
As we become increasingly more aware of the value of our digital identity and personal information, pervasive data collection, misuse scandals, and data breaches are causing a serious trust crisis to arise. People demand more control, transparency, and traceability of their data, they call for stricter regulations on data collection, storage, and processing.
The next decade could be that turning point when governments take legislative action and streamline widespread implementation of new practices and technologies for our security and privacy needs.
One of the most promising solutions in that direction is digital ID, a foundational set of enabling technologies that focus on providing people with full personal data ownership, control, and privacy. Such systems can be pivotal in a wide range of digital interactions between governments, individuals, and businesses. And governments do take steps in that direction.
The U.S. Commerce Department’s National Institute of Standards and Technology (NIST) has awarded grants to multiple initiatives that support the goals of the National Strategy for Trusted Identities in Cyberspace (NSTIC) and seek to provide citizens with secure, resilient, and privacy-enhancing online identities.
Numerous other countries have also initiated the development of their eID systems to help people not only protect their data but also deliver on Goal 16.9 of the Sustainable Development Goals (SDGs) set by the United Nations General Assembly in 2015 which states: “By 2030, provide legal identity for all, including birth registration.”
According to the World Bank ID4D, more than one billion people in the world are unable to prove their identity and therefore lack access to vital services including healthcare, social protection, education, and finance. Worldwide adoption of Digital ID systems can change that.
DNA Digital Data Storage
Over the last few years, the world has witnessed an exponential growth in the Global Datasphere that, according to the forecast of the International Data Corporation, will continue to grow at the annual rate of 61% and reach 175 zettabytes by 2025. Sooner or later traditional and cloud data centers will not have the capacity to effectively store and maintain these staggering amounts of data, not to mention the huge amounts of power they use for the purpose.
Besides, contemporary data-storage devices are not nearly reliable enough to be entrusted with long-term storage. At some point, the world will have to adopt a whole new means of preserving and managing data.
A very promising alternative to all those HDDs, SSDs, and other electronic devices is DNA. Like the real ones — carrying genetic instructions for the development, functioning, growth, and reproduction of all known organisms on Earth — synthesized strands of DNA will be able to store the encoded data in a very efficient, stable, and reliable manner.
The storage capacity and durability of DNA exceeds electronic devices by all means possible. A single gram of synthetic DNA can store over 215 petabytes of data. Moreover, under ideal conditions, such DNA can last for more than 6 million years. Its maintenance does not require much energy either.
Though still at the early stages of development, the technology is already being effectively used to store and manage data with a small number of DNA-data-storage pioneers showing the first results. In 2016, Microsoft managed to store 200 megabytes of data in nucleotide strands of DNA. In June 2019, a startup called Catalog succeeded in encoding all 16 GB of English-language Wikipedia onto synthetic DNA. But if the technology is so great, what’s stopping us from adopting it at this very moment?
Unfortunately, DNA’s ubiquitous practical use as a storage medium is hindered by extremely slow read/write times and huge costs. While reading and sequencing have gotten far less pricey in the last few years, writing remains problematic and ridiculously expensive. Who knows, perhaps through 5-10 years of thorough research and development, DNA will become a ubiquitous storage material that brings long-term data preservation and management to an entirely new level.
The superior interconnectivity of edge computing, the cognitive power of artificial intelligence, extended reality and its immersive possibilities, the convenience of intelligent interfaces, the immutable level of trust set by distributed ledger technology, data security and privacy goals aspired by digital IDs, and the unfathomable potential of DNA as digital data storage — all these technologies are already among us and their further development will undoubtedly shape our future for 2020 and beyond.
To avoid being left behind in the highly competitive digital-transformation race, follow these game-changing technologies, get on board, and prepare to grasp the limitless opportunities they present.
Published at DZone with permission of Andrew Smith. See the original article here.
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