2018 was yet another break-through year in the tech space, from 3D metal printing, duelling neural networks, real-time translation ear-buds through to advances in quantum computing, but what can we all look forward to in 2019?
Here are a selection of techs that we see as being hot in 2019 based on the demand we see from our clients, talking to our friends in the industry and keeping an eye on industry research & papers.
A minefield of complexities to attempt to describe, quantum computing essentially allows a model of computing that is both exponentially scalable and parallel – instead of being able to work on computations in a linear fashion, quantum computers offer the theoretical possibility of working on millions of computations all at the same time.
A smart space is an environment, physical or digital, in which humans and technology-enabled systems are able to interact as an ecosystem. Smart devices alone are a thing of the past – now we look to entire spaces of both technology and humans working together in harmony to increase productivity, accessibility and allow humans to have a life more seamlessly integrated than ever before.
Smart spaces are developing on the backs of individual products developed using AI, edge computing and blockchain, for instance. People can now own smart houses, with all of their appliances and devices connected and able to talk to one another so that the owner can have complete control but also full visibility over everything all at once. In a smart house, your smart fridge can notify you when you run out of milk, which can then trigger your smart phone to place an order for the milk and have it delivered, all without you ever having to lift a finger.
The largest and most extensive example of a smart space is the idea of smart cities – a city which looks to combine residential, business and industrial complexes designed around digital ecosystems.
Blockchain is not new but its applications are becoming ever more widespread. Distributed Ledger tech is having broad applicability, not just within the banking space, but now being used by companies across a variety of functional domains, whether it be from tracking the lineage of conflict precious materials through application in content streaming companies.
It is predicted that pure blockchain will create $3.1 trillion in business value by 2030, based on research by Gartner.
Immersive Technologies and VR
This is the grouping together a number of technologies, including virtual reality (VR), augmented reality (AR) and conversational platforms.
The business use for this tech is endless – already we see clothing brands, for instance, allowing customers to see how items of clothing will look on them using AR. Conversational platforms such as digital personal assistants or AI-driven chatbots, are already reforming the scope of both customer service and carrying out simple tasks. This technology will likely expand out to include many more ways to communicate with devices, such as through facial expressions, and the technology will become even more sophisticated in the ways it is able to converse with users.
Edge computing places information processing, content collection and delivery closer to the source of data. With more and more devices requiring a connection in order to both deliver services and work seamlessly in a smart ecosystem, edge computing continually becomes more of a priority.
A digital twin, as the name suggests, is a digital mirror of a real-life object, system or process. On a large scale, digital twins can also be linked together to create a twin of entire cities, for instance.
The benefit of twins is that it allows businesses to evaluate risk and ‘what if’ scenarios, predict business outcomes, potentially allow for real time monitoring and control and can generally improve business decision making. The robustness and intricacies of the models allow for new and expansive levels of insight, which can have untold potential to assist business strategy going forward.
Artificial Intelligence (AI)
This is nothing new, but the velocity of progress continues to increase. As we saw in 2018, self-learning algorithms dramatically accelerated the historically time-consuming task of training based on large data-sets and this pace of evolution is set to continue.
AI has never been more accessible, with a plethora of free open-source libraries available through to very afforable pay per call services offerred by companies like IBM Watson. This makes it easier than ever to apply AI across different functional domains.
We continue to collect more data than ever. This means that data scientists have, in turn, more data than ever to analyse and draw conclusions from. The sheer amount of data in fact means that analysing all of the possibilities of all of the data has become humanly impossible.
Augmented analytics seeks to prevent businesses from missing out on key insights due to overwhelming data – it allows data scientists to use automated algorithms so that they are able to explore even more possibilities than before.
The largest criticism of augmented analytics is that, whilst they theoretically are able to identify hidden trends within data without bias, humans can unintentionally insert their own bias into algorithms, thereby removing objectivity. Eventually, however, businesses seek to use augmented analytics to objectively and thoroughly parse, analyse and group data so that data scientists are able to develop hypotheses and become more productive in their role.
Autonomous Things and Devices
Autonomous things are being developed everywhere. Gartner have identified five separate types: robotics, vehicles, drones, appliances and agents. They are often developed with AI in order to both automate tasks and allow devices to learn as they age. Virtually every piece of technology on this list will involve automation in some way, as it is the key to allowing true integration of spaces, devices and tasks.
Autonomous things are also being used in a variety of innovative and surprising ways. Companies such as Microsoft for instance have robot security – they use Knightscope K5 robots to patrol car parks.
Although AI cannot yet quite navigate the chaos that is created by humans in the physical world, machine learning means that the technology is growing ever more intelligent and capable. The future possibilities are predicted to come to fruition on an aggressive timescale, in ways that could impact most of the modern connected world hugely.