First, introduce a new technology forecasting tool, The Hype Cycle. The technology maturity curve is a predictive tool proposed and used by Gartner Corporation of the United States. Since 1995, Gartner has begun to use technology maturity curves to predict the development of new technologies. The rationale behind this is the extent to which new technologies are exposed in the media, and the time it takes to predict new technologies from exposure to maturity.
Figure 1 technical maturity curve
The Gartner curve divides a company from germination to maturity into five phases. They are:
The promotion period of the birth of science and technology: the birth of new technology, the rapid increase of media reports, often a lot of irrational rendering, the product's visibility is significantly improved. However, from the perspective of maturity, it is still in the early stage, and new technologies often have many shortcomings, problems and limitations.
Excessive peak expectations: As the media exposure increases, public expectations rise rapidly and become fanatical. The new technology has produced some successful stories, but the corresponding ones are more cases of failure.
The low valley of the bubble: As the new technology fails to meet the public's expectations, the effect is questioned, and the exposure drops rapidly, which is forgotten and ignored.
However, from the maturity point of view, after the first two stages, the new technology has been tested and tested by many parties. People have a more objective understanding of their scope and limitations.
The bright period of steady climb: With the gradual maturity of new technologies and the increase of relevant successful business models, new technologies are no longer fashionable, but they will be recognized by the industry and the media, and they will receive more rational and objective evaluations. Steady improvement.
The peak period of physical production: the benefits and potential generated by new technologies are actually accepted by the market. Relevant support tools and methodologies have entered the mature stage after several generations of evolution. Emerging technologies have also become mature technologies.
From the technical maturity curve, we can see that a new technology has been exposed in the media since the early days of its birth. With the media's screaming, people began to increase their irrational expectations, and the technology fever has further increased. When the heat reached a certain level, people found that the expectations could not be met, and the heat of new technology began to fall back and fell to the bottom. Until the new technology has a certain practical application, and then gradually began to reply, people's expectations return to rationality, and new technologies gradually develop to maturity.
Let's take a look at the global new technology forecast map released by Gartner in 2017.
Figure 2 2017 global technology maturity curve
A total of 32 new technologies are listed in the Gartner curve, but 13 of them are related to artificial intelligence. Forecast the curve today and explore the development of artificial intelligence.
First list the relevant 12 industries: deep learning, machine learning, reinforcement learning, general intelligence, autonomous driving, cognitive computing, commercial drones (UAVs), conversational user interfaces, enterprise taxonomy and ontology management, machines Learning, smart dust, intelligent robots, smart spaces.
From the perspective of the ratio of artificial intelligence in the Gaudner curve, the field of artificial intelligence has developed very strongly. In 2017, the first year of artificial intelligence, in addition to AlphaGo defeated the world champion of Go, there are many powerful results.
Sonnet and TensorflowEager join the open source framework family; Facebook and Microsoft are united to enable interoperability of the AI ​​framework; the Machine Learning as a Service (MLAAS) platform will be everywhere.
In 2017, a groundbreaking paper "AttenTIon Is All You Need" proposed a new model, Transformer, which eliminates the complex processing of recursion and convolution to achieve the latest performance of machine translation tasks.
Artificial intelligence has enormous energy in the field of twelve human intelligence, where deep learning and machine learning can mature in 2-5 years. Deep learning and machine learning are well used in DeepMind's AlphaGo company. In particular, the intensive learning of unsupervised learning has made AlphaGo a new level of intelligence.
Artificial intelligence is a structural concept, a system in which deep learning and machine learning play a central role in the current artificial intelligence ecosystem. Deep learning is a very important underlying technical support in the artificial intelligence ecosystem. Both speech recognition and visual recognition use deep learning as the underlying technology. The third wave of artificial intelligence is mainly due to the breakthrough of deep learning algorithms. Due to the sharing of some open source algorithm frameworks, the technical threshold of artificial intelligence has been greatly reduced, and the exchange, growth and prosperity of deep learning in the industry has been accelerated.
Figure 3 Innov100 artificial intelligence innovation TOP100
Autopilot is a driving behavior that is completed without human intervention. However, the current technology is far from this level. Currently in the state of semi-human intervention, Gartner predicts that the current unmanned to fully automated driving application will take more than 10 years.
At present, the testing and research in the field of unmanned driving are in full swing, and various manufacturers are trying to enter this field. Once the driverless technology matures, the biggest impact is the traditional car manufacturers. Unmanned driving technology is bound to change the way of future travel. As a brain in an unmanned system, artificial intelligence will play a decisive role in addition to hardware support and great computing power.
The general intelligence mentioned here refers to the strong artificial intelligence, that is, human beings can complete various thinking characters, rather than being competent in only one field. For example, AlphaGo is a party in the chess world.
The fields involved in artificial intelligence are included in 2-5 years, 5-10 years, and more than 10 years. Although the artificial intelligence media exposure and heat are still acceptable, but it does not reach a wide range of scene applications that can be replicated, so the development of artificial intelligence will gradually develop steadily.
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