Every year the technology research company Gartner release the ‘Gartner Hype Cycle for Emerging Technologies’. The report identifies and discusses upcoming, developing, and established trends in the industry. The company research and evaluate thousands of technologies and establish where in the cycle the technologies sit, and predict how long until these technologies move from ‘emerging’ to ‘established’. Or, as it’s labelled on Gartner’s Hype Cycle: from ‘Innovation Trigger’ to ‘Plateau of Productivity’.
In previous years the Gartner Hype Cycle has predicted the rise of technologies that now seem commonplace. Innovations such as the internet of things, artificial intelligence and hybrid cloud computing were seen by Gartner as ‘emerging’, but have since become established.
For example, the 2010 Gartner Hype Cycle for emerging technologies had ‘Virtual Reality’ and ‘3D printing as emerging innovations, but in 2017 virtual reality is well-established and we’ve moved on to 4D printing now.
Here are some of the top upcoming trends in the Gartner Hype Cycle for Emerging Technologies, 2017:
Conversational user interfaces
With virtual assistants like Siri and Alexa, we’re already seeing some developments in conversational user interfaces, but Gartner predicts that by 2019 up to one-fifth of users will interact with their phones through voice or text-based conversational commands. Google has already begun to implement Conversational user interfaces within their Analytics programme. Instead of having to use menus and mouse pointers to locate data, users can just type questions like “how much mobile traffic did I get last week?” into the conversational user interface and are given an answer.
Digital twins and smart workplaces
Gartner says that digital twins are on the upwards climb of the innovation trend. A digital twin is an exact digital replication of a physical asset, process, or system. Because the physical asset is connected to the internet it can continually provide health and maintenance updates to its digital twin. This would, for example, let a factory owner know when one of their machines is about to overheat or malfunction. A digital twin can improve safety, optimise costs and provide more in-depth analytics.
Serverless computing is a cloud computing model where pricing is based on the exact amount of computing resources used by an application. There are still actual servers required for this kind of hosting, but it’s called serverless because there is no server management required from the developer. Because serverless PaaS reacts to resource requests on demand, a server owner doesn’t have to predict their usage or scale resources up or down when they’re expecting more or less traffic – serverless PaaS will do that autonomously. This saves costs on actual resources, as well as saving overhead and operational costs.
In an IoT world ‘edge computing’ is where the processing of data collected from a device is performed on the device itself, rather than being sent back to a central cloud location for processing. This will lead to extremely fast processing speeds and will, for example, allow autonomous cars to process information within the car itself, rather than wasting split-seconds sending the data over the internet and back for processing. Edge computing will effectively turn the autonomous car into a moving data centre. Gartner predicts that edge computing is 2-5 years away from being well-established.
It sounds like something out of The Martian, but smart dust is the next big development in IoT and sensory computing. Smart dust devices are microelectromechanical sensors (MEMS) which are connected to the internet wirelessly and collect data on light, pollution, and vibrations among other things. These tiny sensors will revolutionise how internet of things devices report on their environments, but Gartner says they’re still more than 10 years away.
Artificial general intelligence
A machine is classified as having artificial general intelligence when it can successfully perform a task that a human can. There are some tests that machines need to pass to be classed as having artificial general intelligence. These tasks include:
- The Coffee Test: where a machine must walk into a house, find the kitchen and figure out how to make a coffee.
- The Robot College Student Test: where a machine must go to university, take classes, pass tests, and finish with a degree.
- The Flat-pack Furniture Test: where a machine is tasked with reading the instruction manual and then assembling a piece of flat-pack furniture – wouldn’t that be helpful?
Gartner anticipates that artificial general intelligence, sometimes dubbed AI-as-a-service, is still over 10 years away, but the innovation behind the technology is already beginning.
As mentioned earlier, since 2010 technology has added another dimension to printing. Literally. 3D printers have since become well established, but what is new and upcoming are 4D printers. A fair question to ask at this point would be “how is it possible to print in more than three dimensions?” Much like its predecessor, a 4D printer prints an object in three dimensions, with the ‘fourth dimension’ coming from the fact that the object can mould and change shape when heat is added.
For example, a piece of flat-pack furniture could be 3D printed, and when heat is applied, the furniture moulds and assembles itself. That would make a machine’s artificial general intelligence furniture task a lot easier.
There's a lot of new innovative technology documented in the report, but it remains to be seen how long it will be before these trends take off. To read the full report visit the Gartner website.