Gartner lists 10 top tech trends for 2016

 

During a press conference held this Tuesday (20/10), as part of the Symposium/ITxpo 2015, O Gartner, Inc.., a world leader in technology research and advice, has outlined the top 10 technology trends that will be strategic for most organizations in 2016.  

 

Gartner defines as strategic technology trends that have the potential to significantly impact organizations. Factors that denote this impact include the high possibility of interference with the business, end users or IT; the need for large investment; or the risk of being too late to adopt it. These technologies affect companies' long-term plans, programs and initiatives.
 
“The top 10 strategic technology trends identified by Gartner will shape digital business opportunities through 2020. The first three trends address the merging of the physical and virtual worlds and the emergence of the digital fabric. As organizations focus on digital markets, algorithmic business is emerging – and soon these relationships and interconnections will define the future of business. In the algorithmic world, many things happen on a plane where people will be involved in the development of the algorithms, which will be the key to the transformations, the intelligence behind the processes”, explains Val Sribar, Group Vice President at Gartner.
 
Check out the 10 main technological trends for 2016 pointed out by the company:
 
Device mesh – The term 'device mesh' refers to an extensive set of points used to access applications and information or to interact with people, social networks, governments and businesses. It includes mobile devices, wearables (wearable technologies), consumer and home electronics, automotive and environmental devices – such as Internet of Things (IoT) sensors. The focus is on the mobile user, who is surrounded by a mesh of devices that extends far beyond traditional means. While devices are increasingly connected to systems backend across multiple networks, they often operate in isolation. As the mesh evolves, connection models are expected to emerge to expand and enhance the cooperative interaction between devices.

 
User-environment experience – Device mesh lays the foundation for a seamless new user experience and environment. Immersive locations, which provide virtual and augmented reality, have significant potential, but are only one aspect of the experience. The user-environment experience preserves continuity across the boundaries of the mesh of devices, time and space. The experience regularly flows through a set of displacement devices and interaction channels, mixing physical, virtual and electronic environments, as the user moves from one place to another.
 
Designing mobile apps remains an important strategic focus for the company. However, the project aims to provide an experience that flows and explores different devices, including Internet of Things sensors and common objects such as automobiles, or even factories. Designing these advanced experiences will be a big differentiator for Independent Software Vendors (ISVs) and similar companies through 2018.

3D printing - Investments in 3D printing (three dimensions) have already enabled the use of a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceutical and biological materials. These innovations are driving user demand, and practical applications are expanding into more industries, including aerospace, medical, automotive, energy and military. The growing supply of materials will lead to an annual growth rate of 64.1% in enterprise 3D printer shipments through 2019. These advances will require an overhaul of assembly-line processes and the supply chain.
 
Everything information – Everything in the digital mesh produces, uses and transmits information. This data goes beyond textual, audio and video information to include sensory and contextual information. The term 'information from everything' addresses this affluence with strategies and technologies to connect data from all these different sources. Information has always existed everywhere, but often isolated, incomplete, unavailable or unintelligible. Advances in semantic tools such as graph databases and other classification analysis and emerging information techniques will bring meaning to the often chaotic deluge of information.
 
Advanced machine learning – In advanced machine learning, Deep Neural Networks (DNN) move beyond classical computing and information management, creating systems that can learn to perceive the world autonomously. The multiple sources of data and the complexity of the information make manual classification and analysis unfeasible and unprofitable. DNNs automate these tasks and make it possible to address key trend-related challenges. DNNs are an advanced form of machine learning particularly applicable to large and complex datasets, and make smart equipment appear 'smart'. They allow hardware or software-based systems to learn for themselves all the features in their environment, from the smallest details to large abstract classes of scanning content. This area is rapidly evolving, and organizations must assess how to apply these technologies to gain competitive advantage.
 
Autonomous agents and equipment – Machine learning gives rise to a spectrum of smart equipment implementations – including robots, vehicles, Virtual Personal Assistants (APV) and smart advisors – that act autonomously or at least semi-autonomously. While advances in physical intelligent machines such as robots have attracted attention, when software-based they have a faster payback and wider impact. Virtual Personal Assistants like Google Now, Microsoft's Cortana, and Apple's Siri are becoming smarter and are precursors to autonomous agents. The emergence of the notion of assistance feeds the user-environment experience, in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the individual talks to an application, which is really an intelligent agent. Over the next five years we will evolve into a post-application world, with intelligent agents providing dynamic, contextual actions and interfaces.
 
Adaptive Security Architecture – The complexities of digital business and algorithmic economics, combined with an emerging 'hacker industry', significantly increase the threat surface to organizations. Relying on rules-based perimeter defense is not enough, especially given the fact that companies exploit many Cloud-based services and open Application Programming Interfaces (API) for customers and partners to integrate with their systems. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks. Self-protection of applications and analysis of user and entity behavior will help meet the adaptive security architecture.
 
Advanced System Architecture – The digital fabric and smart machines require intense computing architecture demands to make them viable for organizations. This triggers a boost in ultra-efficient, high-powered neuromorphic architecture. Powered by Field Programmable Gates (FPGA) arrays as the underlying technology, it enables significant gains such as running at speeds of more than one teraflop with high energy efficiency. Systems built on Graphics Processing Units (GPU) and FPGAs will function like human brains, particularly suited to being applied to deep learning and other pattern matching algorithms used by intelligent machines. The FPGA-based architecture will enable greater distribution of algorithms in smaller form factors, using considerably less electrical energy in the device mesh, and allowing advanced machine learning capabilities to be proliferated to the tiniest endpoints of the Internet of Things, such as homes, cars, wristwatches and even human beings.
 
Network application and service architecture – Monolithic linear application designs such as three-tier architecture are giving way to an integrative approach of more informal coupling: architectural applications and services. Powered by software-defined application services, this new approach enables web-like performance, flexibility and agility. Microservices architecture is an emerging standard for building distributed applications that support agile delivery and scalable deployment both on-premises and in the cloud. Containers are emerging as a key technology to enable agile microservices development and architecture. Bringing IoT and mobile elements into the application architecture creates a comprehensive model to handle the backend Cloud scalability and the mesh experience of frontend devices. Application teams must build modern architectures to deliver cloud-based utilities that are agile, flexible, and dynamic, with user experiences that are also agile, flexible, and dynamic spanning the digital fabric.
 
Internet of Things (IoT) Platforms – IoT platforms complement the network application and service architecture. Management, security, integration, and other platform technologies and standards are a core set of competencies for building, managing, and securing elements of the Internet of Things. These platforms constitute the work that the IT team does behind the scenes, from an architectural and technological point of view, to make IoT a reality. The Internet of Things is part of the digital fabric, which includes the user experience, and the environment of the emerging and dynamic world of platforms is what makes it possible.