Top 10 Technology Trends for 2018: IEEE Computer Society Predicts the Future of Tech
LOS ALAMITOS, Calif., Dec. 14, 2017 /PRNewswire/ -- Tech experts at the IEEE Computer Society (IEEE-CS) annually predict the "Future of Tech" and have revealed what they believe will be the biggest trends in technology for 2018. The forecast by the world's premier organization of computing professionals is among its most anticipated announcements.
"The Computer Society's predictions, based on a deep-dive analysis by a team of leading technology experts, identify top-trending technologies that hold extensive disruptive potential for 2018," said Jean-Luc Gaudiot, IEEE Computer Society President. "The vast computing community depends on the Computer Society as the provider for relevant technology news and information, and our predictions directly align with our commitment to keeping our community well-informed and prepared for the changing technological landscape of the future."
Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE Computer Society past president, said, "The following year we will witness some of the most intriguing dilemmas in the future of technology. Will deep learning and AI indeed expand deployment domains or remain within the realms of neural networks? Will cryptocurrency technologies keep their extraordinary evolution or experience a bubble burst? Will new computing and memory technologies finally disrupt the extended life of Moore's law? We've made our bets on our 2018 predictions."
The top 10 technology trends predicted to reach adoption in 2018 are:
1. Deep learning (DL). Machine learning (ML) and more specifically DL are
already on the cusp of revolution. They are widely adopted in datacenters
(Amazon making graphical processing units [GPUs] available for DL, Google
running DL on tensor processing units [TPUs], Microsoft using field
programmable gate arrays [FPGAs], etc.), and DL is being explored at the
edge of the network to reduce the amount of data propagated back to
datacenters. Applications such as image, video, and audio recognition are
already being deployed for a variety of verticals. DL heavily depends on
accelerators (see #9 below) and is used for a variety of assistive
functions (#s 6, 7, and 10).
2. Digital currencies. Bitcoin, Ethereum, and newcomers Litecoin, Dash, and
Ripple have become commonly traded currencies. They will continue to
become a more widely adopted means of trading. This will trigger improved
cybersecurity (see #10) because the stakes will be ever higher as their
values rise. In addition, digital currencies will continue to enable and
be enabled by other technologies, such as storage (see #3), cloud
computing (see B in the list of already adopted technologies), the
Internet of Things (IoT), edge computing, and more.
3. Blockchain. The use of Bitcoin and the revitalization of peer-to-peer
computing have been essential for the adoption of blockchain technology
in a broader sense. We predict increased expansion of companies
delivering blockchain products and even IT heavyweights entering the
market and consolidating the products.
4. Industrial IoT. Empowered by DL at the edge, industrial IoT continues to
be the most widely adopted use case for edge computing. It is driven by
real needs and requirements. We anticipate that it will continue to be
adopted with a broader set of technical offerings enabled by DL, as well
as other uses of IoT (see C and E).
5. Robotics. Even though robotics research has been performed for many
decades, robotics adoption has not flourished. However, the past few
years have seen increased market availability of consumer robots, as well
as more sophisticated military and industrial robots. We predict that
this will trigger wider adoption of robotics in the medical space for
caregiving and other healthcare uses. Combined with DL (#1) and AI (#10),
robotics will further advance in 2018. Robotics will also motivate
further evolution of ethics (see #8).
6. Assisted transportation. While the promise of fully autonomous vehicles
has slowed down due to numerous obstacles, a limited use of automated
assistance has continued to grow, such as parking assistance, video
recognition, and alerts for leaving the lane or identifying sudden
obstacles. We anticipate that vehicle assistance will develop further as
automation and ML/DL are deployed in the automotive industry.
7. Assisted reality and virtual reality (AR/VR). Gaming and AR/VR gadgets
have grown in adoption in the past year. We anticipate that this trend
will grow with modern user interfaces such as 3D projections and movement
detection. This will allow for associating individuals with metadata that
can be viewed subject to privacy configurations, which will continue to
drive international policies for cybersecurity and privacy (see #10).
8. Ethics, laws, and policies for privacy, security, and liability. With the
increasing advancement of DL (#1), robotics (#5), technological
assistance (#s 6 and 7), and applications of AI (#10), technology has
moved beyond society's ability to control it easily. Mandatory guidance
has already been deeply analyzed and rolled out in various aspects of
design (see the IEEE standards association document), and it is further
being applied to autonomous and intelligent systems and in cybersecurity.
But adoption of ethical considerations will speed up in many vertical
industries and horizontal technologies.
9. Accelerators and 3D. With the end of power scaling and Moore's law and
the shift to 3D, accelerators are emerging as a way to continue improving
hardware performance and energy efficiency and to reduce costs. There are
a number of existing technologies (FPGAs and ASICs) and new ones (such as
memristor-based DPE) that hold a lot of promise for accelerating
application domains (such as matrix multiplication for the use of DL
algorithms). We predict wider diversity and broader applicability of
accelerators, leading to more widespread use in 2018.
10. Cybersecurity and AI. Cybersecurity is becoming essential to everyday
life and business, yet it is increasingly hard to manage. Exploits have
become extremely sophisticated and it is hard for IT to keep up. Pure
automation no longer suffices and AI is required to enhance data
analytics and automated scripts. It is expected that humans will still
be in the loop of taking actions; hence, the relationship to ethics
(#8). But AI itself is not immune to cyberattacks. We will need to make
AI/DL techniques more robust in the presence of adversarial traffic in
any application area.
Existing Technologies: We did not include the following technologies in our top 10 list as we assume that they have already experienced broad adoption:
A. Data science
B. "Cloudification"
C. Smart cities
D. Sustainability
E. IoT/edge computing
IEEE-CS technical contributors include Erik DeBenedictis, Sandia National Laboratories; Fred Douglis, systems researcher and member of IEEE-CS Board of Governors; David Ebert, professor, Purdue University; Paolo Faraboschi, Hewlett Packard Enterprise Fellow; Eitan Frachtenberg, data scientist; Phil Laplante, professor, Penn State University; and Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE Computer Society past president. The technical contributors for this document are available for interview.
At the end of 2018, we will review the predictions and determine how closely they match up to technology's reality. Check back in December 2018 as we grade our latest predictions.
For past predictions, see news release for 2017 technology predictions and grades.
About IEEE Computer Society
IEEE Computer Society, the computing industry's unmatched source for technology information and career development, offers a comprehensive array of industry-recognized products, services and professional opportunities. Known as the community for technology leaders, IEEE Computer Society's vast resources include membership, publications, a renowned digital library, training programs, conferences, and top-trending technology events. Visit www.computer.org for more information on all products and services.
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