Machine Learning Is Everywhere
Research into machine learning (ML) algorithms has been advancing for many years, but in 2016 we saw it storm onto the mainstream stage. ML algorithms can now be trained on all sorts of data, thanks to the availability of high-powered processors, "big data" collection architectures, and open source software implementations.
We will continue to see ML expand in importance as a fundamental technology driving innovation in every industry. In the context of network technology, ML techniques will be applied to problems that were previously thought to be impractical to solve. The tech talent crunch that we saw in 2016 will get even worse in 2017 as demand rises for the most talented ML scientists and engineers. Combined with SDN and NFV, ML will be a core competency for any vendor trying to build next-generation platforms for vehicular networking, IoT, MEC, cloud, and security.
Shadow IT vs. Security
As consumer technologies become more and more user-friendly and powerful, enterprises have faced increasing levels of "Shadow IT" in which their users bring their own devices, manage their own apps and data, and use their own personal collaboration tools to perform their job. Despite the potential dangers, Shadow IT continues to grow as enterprise IT is unable to compete with features, ease of use, and reliability of consumer services. Shadow IT has become common enough that it even found its way into mainstream news stories in 2016, as illustrated by ongoing discussion of the email habits of candidates in the recent U.S. election.
Of course, in the face of Shadow IT behaviour, corporate info-sec teams will continue to struggle. While some organisations will attempt to legislate security via corporate policy, in 2017 the most enlightened companies will recognise the implicit threat of sub-par IT services. The most successful IT and info-sec teams will collaborate on simultaneously modernising and securing their infrastructure with SDN, orchestrated NFV security services, advanced encryption and identity management, integration of cloud services, and compartmentalisation of local apps.
Networked VR and AR
Virtual Reality (VR) and Augmented Reality (AR) have struggled against technical limitations for decades, but 2016 was apparently the break-out year - consumer VR headsets are available for video game systems just in time for the 2016 holiday season, several popular smartphone brands now have VR functionality, and the release of promising new AR systems is on the horizon.
In 2017, we can expect to see these VR and AR systems focused primarily on entertainment and education. But as the platforms become more established, toward mid to late 2017, we can expect to see experimental applications in communications, data visualisation, and enterprise situational awareness.
We are entering 2017 with excitement and optimism. The future is bright and ours to create. Welcome to the Network Age where the possibilities are infinite. Are you ready?
Sign up for Computerworld eNewsletters.