On August 29, Gartner, the world’s most authoritative IT market research and consulting company, released the 2019 technology maturity curve (Hype Cycle, hereinafter referred to as the “Gartner curve”) of new technologies. To put it simply, this is a curve that describes the changes in social expectations over time after the emergence of new technologies. It can show the degree of deviation between the market enthusiasm of new technologies and the actual development, so as to help companies make better use of mature technologies and find potential opportunities.
As early as 1995, Gartner designed this analysis tool. They combined the judgments of analysts, experts and industry professionals to draw a curve with ups and downs, used to list the most eye-catching and promising new technologies of the year, and predict the time required for them to mature. The Gartner curve is composed of two curves superimposed, one is the “hype level” curve that reflects the public’s false high expectations for technology, and the other is the engineering or commercial maturity curve. Basically, the new technology of throwing concepts and “storytelling” will be enthusiastically sought after by the media at the beginning, but once it is verified by the market, the bubble that the new technology previously promoted will slowly be blown away, and then it will enter the “high drive and low move.” The stage later gradually climbed to the mature stage.
From a coordinate point of view, the Y-axis represents people’s expectations for new technologies, while the X-axis corresponds to time. From left to right, there are “trigger period”, “expansion period”, “trough period”, “recovery period” and ” Five stages of maturity. In addition, each technology is marked with the number of years required to reach the mature stage of production.
This year, Gartner selected 29 out of 2,000 technologies, and from this it summed up five innovative technology trends that corporate decision makers should take into consideration. Brian Burke, vice president of research at Gartner, pointed out in an interview with CIO Dive that “artificial intelligence has penetrated into all other trends.”
Five outstanding trends
Sensing and Mobility
With the development of sensing technology and AI, autonomous robots will be able to better understand the surrounding environment. The trend of sensing and mobility is characterized by the increasing ability of machines to move and manipulate objects. For example, 3D sensing cameras are responsible for collecting large amounts of data, and AI can insight into these data and apply them in various scenarios. For example, light-cargo delivery drones will be able to navigate and manipulate goods better.
In addition, companies betting on this technology trend should also consider augmented reality cloud (AR cloud), flying autonomous vehicles (flying autonomous vehicles), and L4 and L5 autonomous driving levels (autonomous driving Levels 4 and 5).
“(Human ability enhancement) is not to replace humans in making decisions, but to provide guidance when they perform tasks. This enhancement is like putting humans on prostheses, whether in a physical or cognitive sense.” Burke Said. Such enhancement technologies include biochips and emotion AI. Among them, emotional AI is being used in insurance fraud detection, which is different from the previous need to combine claims analysis, computer programs and manual detection. With emotional AI, insurance companies can complete the detection through the caller’s statement.
This trend also includes personification (personification), enhanced intelligence (augmented intelligence), immersive workplace (immersive workplace) and biotechnology (cultivating tissue or artificial tissue).
For decades, classic core computing, communication, and integration technologies have developed rapidly through improvements to traditional architectures, resulting in faster CPUs, higher storage densities, and ever-increasing throughput. Then classic computing and communication will use a completely new architecture. For example, the next-generation cellular network standard 5G will rely on core slicing and wireless edge, and these new architectures can promote a series of progressive technological improvements-making low-Earth orbit satellites (Low-Earth Orbit) earth-orbit satellite systems) can operate at an altitude within 1200 miles from the ground. They will radiate to 48% of users who have not yet connected to the network, and will have a huge impact on social significance and economic benefits.
In addition, post-classical computing and communications also include technologies such as next-generation memory and nanoscale 3D printing.
Enterprises should break through the limitation of only focusing on their own industrial chain, and share and cooperate with more enterprises, people and things across industries. The digital ecosystem is breaking down this traditional value chain and developing more seamless and flexible connections. Therefore, companies will look for solutions on the blockchain.
The key technologies that companies can consider include digital operations (DigitalOps), knowledge graphs, synthetic data, decentralized web, and decentralized autonomous organizations.
Advanced analytics uses more sophisticated tools to automatically or semi-automatically verify data or content, and it is often beyond the scope of traditional business intelligence (BI). For example, transfer learning focuses on storing existing problem-solving models and applying them to other different but related problems. For example, the model used to identify cars can also be used to improve the ability to identify trucks. This advanced analysis can provide deeper insights, forecasts, and recommendations.
New technologies falling on the Gartner curve also include adaptive machine learning (adaptive ML), edge AI, edge analytics, explainable AI, and artificial intelligence platform as a service (AI PaaS), generative adversarial network and graph analytics.
On this year’s Gartner curve, autonomous flying cars, L4 and L5 level autonomous driving, biotechnology, biochips, knowledge graphs, edge artificial intelligence, artificial intelligence PaaS and 5G coincide with last year. Among them, 5G has entered the expected expansion period this year, and there are still 2-5 years before the technology is mature. Also entering this interval are edge artificial intelligence, low-Earth orbit system, L5 level autonomous driving, edge analysis, AI PaaS, biochip and chart analysis. Sliding into the trough are next-generation storage, 3D sensing cameras, and L4-level autonomous driving. Among them, the latter is marked as more than 10 years away from technological maturity.
In addition, this year Gartner put 21 new technologies on the curve, “eliminating” technologies like the Internet of Things and blockchain that fell in the expansion period last year. “This year Gartner will focus on the manifestation of new technologies,” foreign media Computerworld commented, “but this does not mean that the “old” technology is no longer important.” For example, the Internet of Things is “decomposed” into a branch of 3D technology. Sensing cameras and blockchain technology are embodied by technologies such as distributed autonomous organizations.
What remains unchanged is that this year’s Gartner curve still emphasizes the reshaping of enterprises by AI.
The future picture described by Gartner is that by 2029, in all major industries, you can see that leading companies are using advanced analytics and using automation to increase their workforce. These companies will also use blockchain to cooperate with multiple parties in a complex digital ecosystem, and use sensing technology and next-generation computing to maximize efficiency, and then stand out from the fierce competition.
In an interview with CIO Dive, Brian Burke, vice president of research at Gartner, pointed out that “artificial intelligence has penetrated into all other trends.” AI can pick and choose massive amounts of data more finely, provide decision-making support, replace part of the manpower, and promote the development of other technologies. There is no doubt that AI will have a huge impact on the development of business.
But when it comes to using AI, companies first need to overcome the following obstacles: “The key to making any AI solution work is computing power, algorithms, massive amounts of data, and employees who are proficient in using AI.” said Soumendra Mohanty, executive vice president of IT company L&T Infotech. According to Gartner data, by 2020, AI will create 2.3 million jobs. At the same time, 50% of organizations will lack relevant AI and data analysis talents.