Paper Example on Gartner Hype Cycle

The Gartner Hype Cycle segments technologies which will revolutionize the world in the future. Importantly, it's highly the anticipated period when each technology is likely to be adopted fully into human life. These technologies are showing a high degree of providing a competitive edge for business in the next decade, with some becoming highly dominant. However, all will not just happen at the same time. There are those who will likely happen within the next five years, with others having a 5 to 10 years period to be adopted by business, and others having more than a decade to start being part of any business. Below are some of the technologies which Gartner Hype Cycle anticipates to be adopted by business within the next five years (Panetta, 2018).

Machine learning This falls under artificial intelligence, a field which will revolutionize business technology within the next five years that is if it is not doing so apparently. Machine learning involves having computers with the capabilities of executing tasks without necessarily having to be programmed (Starmford, 2017). Machine learning examines and makes algorithms which can extract data from different sources and make data-backed decisions. Gartner Hype Cycle anticipates this to be a common activity in the next five years in business. The second technology which is also related to machine learning is deep learning, which employs the machine learning methodology which is based on data representations, as opposed to task-specific methodologies relied on machine learning.

The third is edge computing, which is defined in the context of the industrial internet of things (IIoT). In the context of IIoT, edge computing is placing computing infrastructure in the peripherals of sources of data in the industrial set up. This technology will enable the gadgets to collect data from the sources and send it to cloud. This technology is being pursued by industrial complexes which have hit the end of improving efficiency and performance through approaches like lean management and six sigma (Verdoux, 2015). They see the technology as a source of competitive advantage.

Augment data discovery comes fourth, which will give businesses an opportunity to identify hidden issues and patterns with data. Augmented data discovery will allow business go beyond data monitoring, enabling them to analyze and identify facts critical to business success, like potential markets, cost reduction strategies, among other issues which will give the business some competitive advantage. Lastly, we will have the Commercial UAVs (Drones) in business within the next five years. Drones are set to be used in commercial aspects like surveillance, filmmaking and journalism, surveying and even cargo transport. The technology is already in use, but very few firms are using it. It definitely stands to be common in next five years.

With the sated technologies anticipated to come to fruition in next five years, there are those who will surely be dominant. The three leads are machine learning, commercial UAVs, and deep learning, based on their potential market size, and probable value to businesses, including small ones. Companies like Amazon are already utilizing Commercial UAVs to deliver cargo to far away destination. In next five years, when it becomes very cheap to acquire and obtain these gadgets, even the local groceries will start delivering using the same. It will be the primary delivery options for most retailers and wholesalers. The next technology will be machine learning. Industries are removing people to replace them with high-level intelligent computers which can collect data, think and act appropriately. Machine learning will affect several industries, particularly education and healthcare. Robots, which are elements of machine learning can diagnose patients, take data and compare it millions of others, offering a faster, more precise diagnosis than a human doctor. When it comes to surgeons, they are tipped to be near perfect. Similarly, with smartboards, tablets, laptops, projectors and other technologies already in a classroom setup, machine learning will disrupt education in a bid way. Robotic teachers have the abilities to offer differentiation in the classroom in scale not possible with a human teacher. It can collect, compile, analyze and compare against difficulties, helping develop solutions customized for the student (Read, 2018). That means better results with a very short time. Deep learning will also become dominant as businesses seek to utilize data and come up with useful social and business decisions.

Exceptional mathematics and science skills will definitely be useful in aiding these technologies. As an engineer, one can help in developing the machines which can lay all the roles stated above. They may be intelligent, but their intelligence originates from man, which builds them. With further training, I believe I have the skills to be a developer on leading developers around the globe. Data analytics and predictions from deep learning will want one to execute them. If the analysis shows that certain goods are not selling, then they are abandoned, that needs someone knowledgeable in the area. The same would be said with edge computing; it is those know who will be able to understand the analysis and predictions provided by these technologies. I am therefore well prepared to be part of the technological transformation.

References

Panetta, K. (2018). Top Trends in the Gartner Hype Cycle for Emerging Technologies, 2017. Smarter With Gartner. Retrieved 2 February 2018, from https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/

Read, G. (2018). 5 Industries Machine Learning is Disrupting - Import.io. Import.io. Retrieved 2 February 2018, from https://www.import.io/post/5-industries-machine-learning-is-disrupting/Starmford. (2017). Gartner Identifies Three Megatrends That Will Drive Digital Business Into the Next Decade. Gartner.com. Retrieved 2 February 2018, from https://www.gartner.com/newsroom/id/3784363

Verdoux, P. (2011). Emerging Technologies and the Future of Philosophy. Metaphilosophy, 42(5), 682-707. http://dx.doi.org/10.1111/j.1467-9973.2011.01715.x