Top Technology Trends

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Regardless of whether you’re a diehard tech obsessive, always after the latest devices, or a laid-back “average” consumer, if you’re like me, you can’t help but look forward to the tech developments and trends that invention ahead. After a year with unexpectedly high sales for smart speakers and virtual reality, as well as the introduction of several new phones and tablets.
As a marketer, my viewpoint often turns to how we can use these new technologies and trends to better interconnect with our audiences.
The top 10 technology trends predicted to reach acceptance in 2018 are:

1. Deep learning (DL):

Machine learning (ML) and more precisely DL are already on the limit of revolution. They are usually adopted in data centers (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 decrease the amount of data broadcast back to datacenters. Applications such as image, video, and audio recognition are already being deployed for a range of verticals. DL greatly depends on accelerators and is used for a variety of assistive functions.

2. Digital currencies:

Bitcoin, Ethereum, and newcomers Litecoin, Dash, and Ripple have become generally traded currencies. They will continue to become a more broadly adopted means of trading. This will move toward cybersecurity because the risks will be even higher as their values rise. On the other hand, digital currencies will continue to enable and be enabled by other technologies, such as storage cloud computing 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 important for the adoption of blockchain technology in a broader sense. We expect the 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 commonly adopted use case for edge computing. It is driven by real requirements. We expect that it will continue to be adopted with a broader set of technical offerings enabled by DL, as well as other uses of IoT.

5. Robotics:

Even though robotics research has been performed for many decades, robotics adoption has not succeeded. However, the past few years have seen the increased market availability of consumer robots, as well as more urbane military and industrial robots. We predict that this will trigger extensive adoption of robotics in the medical space for caregiving and other healthcare uses. Combined with DL robotics will further advance in 2018. Robotics will also motivate further evolution of beliefs

6. Assisted transportation:

While the promise of fully self-directed vehicles has slowed down due to numerous obstacles, a limited use of automatic assistance has sustained to grow, such as parking assistance, video recognition, and alerts for leaving the lane or recognizing sudden obstacles. We expect 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 assumption in the past year. We anticipate that this trend will grow with new user interfaces such as 3D projections and movement detection. This will allow for connecting individuals with metadata that can be seen subject to privacy configurations, which will continue to drive international policies for cybersecurity and privacy.
With the growing development of DL robotics technological assistance and applications of AI technology has moved beyond society’s ability to control it easily. Required guidance has already been deeply analyzed and rolled out in various aspects of design and it is further being applied to autonomous and intelligent systems and in cybersecurity.

8. Accelerators and 3D:

With the end of power scaling and Moore’s law and the shift to 3D, accelerators are evolving as a way to continue improving hardware performance and energy efficiency and to decrease costs. There are numerous of existing technologies (FPGAs and ASICs) and new ones (such as memristor-based DPE) that hold a lot of potential for accelerating application domains (such as matrix multiplication for the use of DL algorithms).

9. Cybersecurity and AI:

Cybersecurity is becoming essential to everyday life and business, yet it is gradually hard to manage. Exploits have become tremendously sophisticated and it is hard for IT to keep up. Pure automation no longer suffices and AI is required to develop data analytics and automated scripts. It is estimated that humans will still be in the loop of taking actions; hence, the relationship to ethics. But AI itself is not safe to cyber-attacks. We will to make AI/DL techniques more robust in the presence of adversarial traffic in any application area.

10. Existing Technologies:

We did not include the following technologies in our top 10 list as we assume that they have already knowledgeable broad adoption:

A. Data science
B. “Cloudification”
C. Smart cities
D. Sustainability
E. IoT/edge computing

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