October 27. 2015
Every year Gartner Inc. analysts highlight the top 10 technology trends for the upcoming year and present the findings at the annual Gartner Symposium/ ITxpo. The findings are defined as the "top technology innovations which will have a significant impact on the organisation". The conference took place this month in Orlando, Florida and Item Shark has summarised the top 5 trends below.
1. The Device Mesh
As we continue to expand the number of devices we carry and use, analysts predict that there will be an increasing focus on how we can combine the use of all the devices for a better user experience. While devices have been linked through cloud software and back end systems, the devices themselves have operated largely in isolation. Gartner predict the expansion of connection models which allows for cooperative interaction.
2. Ambient User Experience
The improved connectivity of devices introduces an ambient user experience, where augmented and virtual reality become real possibilities and the aim becomes a seamless experience across all devices. This includes not only mobile devices but automobiles and home software.
3. 3D Printing Materials
3D printing has gained increasing traction in the past decade but has yet to trickle down to mainstream society. Gartner suggested that improved machinery and an expanded list of materials suitable for printing will lead to wider usage. Already 3D printed materials are being used in the aerospace, automotive, medical and energy sectors with demand steadily increasing year on year.
4. Information of Everything
The device mesh produces an increasing amount of data and information of everything describes a world where data about our lives are captured and stored in vast quantities each day. Strategies and technology will be required to link and ensure secure usage of all the data and Gartner suggest their will be a competitive market emerge in this area.
5. Advanced Machine Learning
Advance machine learning refers to the evolution of technology to move beyond classic information management to create systems which can autonomously learn to understand the world on their own. DNNs (Deep Neural Nets) are described as an advanced machine learning used in large datasets, and will be the main driver of the evolution.