October 08, 2015
Top 2016 Technologies
By: Phillip Redman

Each year at this time, the research firm, Gartner, Inc. has its annual Symposium and IT Expo in Orlando, FL, where almost 10,000 people in the tech and IT industry converge. (Disclosure: I worked as an analyst at Gartner and attended and spoke at many of these events.) Among hundreds of presentations one of the most popular (around 2,000 people watch this presentation every year) is the “Top 10 Technology Trends” for the next year. Gartner analyst spend months debating over which top technology trends will make this list, a list often picked up and publicized widely. Last year’s trends were pretty broad and included 3D Printing, Internet of Things (IoT), Cloud/Client Computing, among others. No doubt these were pretty big this year. So what’s in store for 2016?

This year Gartner’s list of top technologies for 2016 has gone a little deeper. Its top 10 for 2016 includes (some have explanations where the definition may not be apparent):

  1. The Device Mesh--The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses.

  2. Ambient User Experience--The device mesh creates the foundation for a new continuous and ambient user experience.

  3. 3D Printing Materials

  4. Information of Everything--Everything in the digital mesh produces, uses and transmits information.

  5. Advanced Machine Learning--In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own.

  6. Autonomous Agents and Things--Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner.

  7. Adaptive Security Architecture

  8. Advanced System Architecture--The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations.

  9. Mesh App and Service Architecture--Monolithic, linear application designs (e.g., the three-tier architecture) are giving way to a more loosely coupled integrative approach: the apps and services architecture.

  10. Internet of Things Platforms--The management, security, integration and other technologies and standards of the IoT platform are the base set of capabilities for building, managing and securing elements in the IoT.

Let’s take a deeper look into a couple of these and think about what the impact could be.

Advanced Machine Learning is one that both thrills and scares. There have been recent advances in this area, and a wide array of capabilities. Some may be simple and may improve already existing functions. Foe example, Apple confirmed the purchase of advanced machine learning firm Perceptio, a startup focused on bringing advanced image-classifying artificial intelligence to smartphones by reducing data overhead typically required of conventional methods. Perceptio specializes in deep learning, an arm of machine learning that relies on pattern-based processing to analyze and categorize input. All this to better categorize your photos! Driven by advances in processing and advanced coding, machines are even learning—from other machines. In this case, one robot can learn a process from another, simply by observing. This is leading to thinking machines. Gartner predicts one day these machines can replace thinking-based jobs and skills versus the physical ones robots do today (in car manufacturing, for example). One day companies may be hiring robots to do their consulting for them!

Gartner also goes deeper into IoT, basing three of its technology predictions on device mesh, IoE and IoT platforms (see above). Companies are looking today at what the solutions are for IoT, because often designing these are complex, due to the number of technologies and components involved. Using that information, all the data captured from processes, machines and people—will no doubt take analytics and analysis to provide recommendations to improve business processes. This is an area that will be at the top of technology lists for years to come.

Companies need to be innovative, but often choosing where to start is a problem. Lists provide a fun debate about what’s hot and potentially, what’s impactful for the next year. What’s on your list, and how does that relate to your budget? We’d love to hear from you.

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