IEEE: The top 10 technology trends for 2019
In addition to their Top 10 Technology Trends for 2019, say the researchers, this year they also review additional technologies that have not yet reached broad adoption and which will be revisited next year, as well as some technologies that have already achieved broad adoption.
“The Computer Society’s predictions, based on an in-depth analysis by a team of leading technology experts, identify top technologies that have substantial potential to disrupt the market in the year 2019,” says Hironori Kasahara, IEEE Computer Society President. “The technical community depends on the Computer Society as the source of technology IP, trends, and information. IEEE-CS predictions represent our commitment to keeping our community prepared for the technological landscape of the future.”
Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE Computer Society past president (2014), adds, “In 2019 we expect to see ever-increasing adoption of deep learning accelerators in the areas of transportation, advanced security, and technologies for humanity. Fueled by advanced materials, adoption of virtual reality and the Internet of Bodies will stretch the future to new unknowns. We are excited about our predictions and the bets we have made for 2019’s technology trends.”
The organization’s top 10 technology trends for 2019 are:
- Deep learning accelerators such as GPUs, FPGAs, and more recently TPUs. The development of these technologies will allow machine learning (or smart devices) to be used in many IoT devices and appliances.
- Assisted transportation. Assisted transportation is already very useful in terms of wide recognition and is paving the way for fully autonomous vehicles. This technology is highly dependent on deep learning accelerators (see #1) for video recognition.
- The Internet of Bodies (IoB). IoT and self-monitoring technologies are moving closer to and even inside the human body. These devices yield richer data that enable more interesting and useful applications, but also raise concerns about security, privacy, physical harm, and abuse.
- Social credit algorithms. These algorithms use facial recognition and other advanced biometrics to identify a person and retrieve data about that person from social media and other digital profiles for the purpose of approval or denial of access to consumer products or social services.
- Advanced (smart) materials and devices. Novel and advanced materials and devices for sensors, actuators, and wireless communications, such as tunable glass, smart paper, and ingestible transmitters, will create an explosion of exciting applications in healthcare, packaging, appliances, and more.
- Active security protection. A new generation of security mechanisms for protecting computer systems is emerging that uses an active approach, such as hooks that can be activated when new types of attacks are exposed and machine-learning mechanisms to identify sophisticated attacks.
- Virtual reality (VR) and augmented reality (AR). Gaming is clearly a driver of these technologies, with other consumer devices becoming affordable and commonplace. VR and AR technologies are also useful for education, engineering, and other fields.
- Chatbots. These artificial intelligence (AI) programs simulate interactive human conversation using key pre-calculated user phrases and auditory or text-based signals. Chatbots have recently started to use self-created sentences in lieu of pre-calculated user phrases, providing better results.
- Automated voice spam (robocall) prevention. Spam phone calls are an ongoing problem of increasing sophistication, such as spoofing the caller ID number of the victim’s family and business associates. However, emerging technology can now block spoofed caller ID and intercept questionable calls so the computer can ask questions of the caller to assess whether he or she is legitimate.
- Technology for humanity (specifically machine learning). Large-scale use of machine learning, robots, and drones will help improve agriculture, ease drought, ensure supply of food, and improve health in remote areas. “Sensors everywhere” and advances in IoT and edge computing are major factors contributing to the adoption of this technology. Recent events, such as major fires and bridge collapses, are further accelerating the urgency to adopt monitoring technologies in fields like forests and smart roads.
Other promising technologies that the organization felt will reach broad adoption sometime after 2019 include digital twins, real-time ray tracing, and serverless computing. Some technologies that the organization felt had already reached broad adoption include Kubernetes, Docker, and edge computing.
For the IEEE Computer Society’s past predictions, see the 2018 technology predictions, as well as the 2018 predictions scorecard for the final evaluation and grades of their predictions.
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Top five cybersecurity trends for 2018
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