First came Virtual Reality (VR), which happened to completely redefine the way we played video games or undertook training for learning something new. Then came Augmented Reality (AR), which enabled us to explore what’s around us with greater details and insight.
Now, Extended Reality (XR) takes it all a notch further by combining both technologies to reveal possibilities that heighten the momentum of the applications that they currently serve, as well as delve further into more industries to explore newer applications.
Besides creating environments that provide true-to-life experiences sans the need to be physically present somewhere, XR and the entire immersive experience trend aims to completely remove distance as being a barrier for connecting, sharing or doing pretty much anything.
Whether it’s to preview products or offer remote training, immersive experiences are gaining more popularity among developers and business owners alike. Think of it as maintaining a remote software development team – only much better than routine video calls and cloud-based document sharing.
While XR focuses on providing an experience in the absence of a physical object, how about complete liberty at the hands of a physical object? This is what autonomous cars are out to achieve. While many other devices, such as parking robots are also being developed to be completely autonomous thanks to the wonders of Artificial Intelligence, autonomous cars have been receiving most of the hype in this subject.
With numerous automobile manufacturers having jumped into the bandwagon of researching on and developing autonomous cars, many other intricacies have since come into play. This brings us to our next topic, and the steadily progressive trend of…
So what is Citizen AI, and how does it differ from, well, just AI? As Artificial Intelligence and Machine Learning systems train themselves to imitate the human way of thinking, much speculation arises about the morality of each decision made. In spite of attempting to be as human-like as possible, AI is still generated by a computer program. So who’s responsible?
In the case of autonomous cars for instance, some manufacturers have devised policies where they shall hold themselves liable in certain situations when an autonomous decision causes damage to the vehicle or its occupants.
This is the theory behind Citizen AI, where organizations are encouraged to not just build AI-backed systems, but also raise them to act responsibly. Lately, various ethical factors surrounding today’s technological advancements have been receiving much attention – and Citizen AI is only one of them.
Big data, and the process of churning out business-worthy numbers a.k.a data science, is of utmost importance in today’s digitally driven world, without a doubt. But as a business owner, have you ever stopped to think how accurate all this data actually is?
While sensors, wearables and a host of other gadgets are perfectly capable of recording the statistics we need, there have been numerous occasions where discrepancies have been recorded. Making business decisions based on inaccurate data isn’t just going to be unproductive, but can even pose serious financial risks akin to a cyber-security breach. Organizations are now being encouraged to adopt data intelligence methods that can help them verify the accuracy of their data, before they make any data-driven business decisions.
As far as the integrity of data goes, generating unbiased results are also of equal importance. AI-based algorithms are sometimes known to be partial towards the company it has been developed for, and Augmented Analytics is helping to change that. Unlike AI simply delivering results based on the data that has been fed to it, Augmented Analytics challenges the status quo by introducing and testing hypotheses into the system.
The accuracy of data is given another spin with the rising popularity of Citizen Data Scientists who, unlike their professional data scientist counterparts aren’t as technically skilled, but possess in-depth industry knowledge to help make sense of all the data available.
Organizations are welcoming fresh perspectives from subject matter experts across various frontiers, which makes the Citizen Data Scientist profession gain all the more interest amongst discerning individuals in any industry. Plus, they’re way cheaper to hire than professional data scientists, making it a tempting prospect for organizations furthermore.
While every bespoke enterprise software product is customized based on an organization’s requirements, it is still done so over the base of the software product. This means that, while some functionalities are tweaked to serve your business’s unique needs, you will still be using the bulk of the basic software.
What if every feature and functionality was individualised – and made into an API? That’s what Microservice infrastructure is all about. While this trend has been around for some time, it has been gaining recognition as more businesses are joining hands as partners, in order to provide consumers with superior quality products and services under one roof.
Through Microservices and its concept of modular, API-based functionalities, all businesses have to do is share their API, which can be integrated into their partner’s digital platform – and vice versa. This makes partnerships way more versatile, as end-to-end software or mobile app development need not be carried out over each business partner’s individual digital platforms.
Originally deployed to manage Bitcoin transactions, Blockchain technology has peaked the interests of business owners and tech enthusiasts alike. Featuring transparent and secure ledgers that are run via peer-to-peer networks, the aspect of a decentralised database that is open for anyone to see makes Blockchain technology a tempting prospect for use in other industries too.
What’s more, modifying a transaction after it has been recorded on the Blockchain ledger is nearly impossible, as the ledger is open to the public and every transaction is verified by every single user on the platform, before it is added onto the ‘chain of blocks’. This thereby prevents tampering, which makes Blockchain highly secure, as a result.
Other industries are keen to adopt Blockchain technology in order to heighten security and transparency within organizations and their stakeholders. Examples include the government (for elections and voting) or healthcare (to store patients’ medical records).
Cloud computing has been quite the rage for a while, what with the absence of physical storage environments and affordable systems from third-party providers. However as more devices get digitised, and more importantly, stay connected to the cloud for functioning optimally, there’s only so much that cloud computing can accommodate.
With storage restrictions and downtime while sending and receiving data, the expectation from devices to operate instantaneously can fall short. That is why Edge Computing is a notch above its cloud counterpart, as it facilitates immediate responses without waiting for data to pass into and out of the cloud.
Edge Computing has already been applied in numerous fields, such as traffic control and wind power. Alleviating the need for cloud storage and round-the-clock connectivity to the cloud, it won’t be surprising to witness Edge Computing introduce a complete overhaul to today’s hardware infrastructure within businesses, and also how various IoT devices function in general.
While Edge Computing removes the need for cloud-based storage and real-time connectivity, Quantum Computing redefines how tasks are processed all together. Unlike classical computers that utilize binary digits, Quantum computers use qubits, which are interchangeable. This therefore enables Quantum computers to process calculations much faster.
But the Quantum computer’s speed isn’t the only factor that renders it superior to its classical counterpart. The key aspect that differentiates Quantum computers is the fact that it can detect patterns that are hardly visible within data, owing to its qubit theory – while classical computers only detect obvious patterns within data, and nothing more.
Due to Quantum computing’s dynamic processing systems, it is already being applied to industries such as finance, to detect favourable investment opportunities for example. As Quantum computers can detect even the minutest patterns within data sets, it proves ideal for discovering things such as new medicines – at the fraction of the time it would’ve otherwise taken.
While the applications of Quantum computing are currently narrowed down to only a few industries such as chemistry, finance and location-based services, the qubit technology has massive potential to immerse itself in any market sector that requires smart, intuitive computing for solving some of our world’s biggest problems.
Natural Language Processing
On a global scale, we have been seeing the rise of numerous voice command systems, all of which are uniquely personified and boast of adhering to every instruction given to it. From ordering pizza to playing your favourite song, these voice-based search facilities have been developed by some of the world’s leading tech giants, each branding their search systems as an actual person, who happens to have their own name and can be spoken to just like you would speak to another human being.
The technology of NLP has extended far beyond voice-based search. It has also been the driving force behind translating webpages online, or suggesting related items based on what you type. Have you noticed how some e-mail providers suggest responses to an e-mail you have received? This is one such use case of NLP.
Apart from that, NLP has also made Sentiment Analysis possible. By enabling brands to ‘listen’ to their consumers and know what they think about a product or service beyond the boundaries of a company’s social media profile and official hashtag, Sentiment Analysis, and subsequently NLP, are both paving their own ways into the business environment. This enables marketers to tailor their strategies into those that provide accurate data of their consumers (this once again implies data integrity) and provide customer-centric products and services at the same time.
Instead of a traffic warden, how about a sensor that controls traffic lights and flow, depending on factors such as time of day and the amount of congestion on roads? This is already a reality in several cities around the world. But that’s not all – from motion sensors that switch lights on and off, to electric garbage trucks, much is changing within our landscapes owing to rapidly advancing technology.
Smart spaces use a combination of technologies, most of which have been mentioned above in this article. While Edge computing can facilitate instant responses in the absence of connectivity lag and cloud storage, Citizen AI can hold itself accountable for the actions that it manifests.
What’s more, every smart device that operates to execute orderly workings of its surrounding area is also a repository of important data, which can then be transferred over to the cloud for analysis and the improvement of smart spaces.
This also ties in the Internet of Things, as all the devices that operate to make smart spaces a reality are indeed smart devices which operate autonomously, and/or can be controlled remotely by an external entity.
While we’ve covered 10 of the hottest technology trends that are bound to dominate 2019, it’s useful to keep in mind that many more still exist, albeit being much smaller than the ones mentioned here. What’s more, each trend is constantly on the works, which makes it safe for us to presume that the tech industry will never be short of things to look forward to – be it in the near or distant future!
Which trend would be the most powerful, and revolutionary? We’ve already given you our lowdown – and will now leave it up to you to decide!