Artificial intelligence in the broad sense refers to the effect produced by the realization of human thinking through computers. It is a description and construction of an intelligent agent that can understand the surroundings and take actions; The artificial intelligence in narrow sense includes the artificial intelligence industry (including various value systems such as technology, algorithms, and applications) and artificial intelligence technologies (using machines to help, replace, or even partially surpass human to realize functions of understanding, recognition, analysis, and decision-making).
The industrial revolution brings automation to the craft industry, and machine learning automates the machine itself; The open source environment can significantly reduce the technical threshold of artificial intelligence; Visual perception gradually realizes its commercial value, and visual cognition remains to be developed.
National policy strongly supports the artificial intelligence industry, pointing out that artificial intelligence must reach the top level in the world. But it pays less attention to the moral problems and threats caused by artificial intelligence.
In the future, there will be more room for the development of complete behavioral planning or decision-making. In addition to cutting-edge algorithms, commercial barriers depend on comprehensive construction of products, services, and markets, etc.
There will be no shortage of jobs in the future, and the technological revolution will improve the overall welfare of the society. The core values of artificial intelligence are cost reduction and human wisdom preservation.
Comparison of Investment, Financing and Patents in the Field of Artificial Intelligence in China and the U.S.
According to CB Insights data, the total amount of financing for global artificial intelligence startups reached a record high of US$15.2 billion in 2017. Chinese companies and American companies accounted for 48% and 38% respectively, ranking the first and the second, respectively. In terms of patent publications, the numbers of titles or abstracts of patent publications which contain “artificial intelligence” in China increased from 328 in 2016 to 641 in 2017. The numbers in the United States increased from 108 in 2016 to 130 in 2017. However, judging from the innovation of the publications, China still lags far behind the United States.
Proportions of the Financing Amount of American And Chinese AI Startups in 2017
48% Proportion of the financing amount of Chinese companies.
38% Proportion of the financing amount of American companies.
2013–2017 Number of Artificial Intelligence Patent Publications in China and the United States
Knowledge graph technology aims to describe various entity concepts and their relationships. Usually, “entity-relation-entity” form a triplet, and each entity also has its corresponding “attribute.” Large-scale knowledge graph usually contains hundreds of millions of entities, tens of billions of attributes, and hundreds of billions of relations. They are from a large amount of structured and unstructured data mining. Based on the specialized knowledge graph and the natural language understanding technology built on it, the machine can fully utilize perform the functions of reasoning and making judgment, accurately answer questions and extend the scope of intelligence.
According to the anthropomorphic research and development concept of autonomous driving, the principle of autopilot system has five layers, which are perception-cognition -decision making-control-enforcement. It processes and integrates the information gained through sensors, get a full understanding of the overall situation, make decisions through algorithms and then generate execution instructions by the control system. In this entire process, vehicles can exchange information with the outside world (such as road facilities, other vehicles, etc.) via V2X (Vehicle to Everything) communication, help the vehicles to acquire real time information of a larger environment and to solve four problems, namely: Where am I? What is around? How will the environment change? What can I do?”.
Public Security Sector
Computer vision, speech recognition, machine learning and many other intelligent technologies can realize identification via multiple biological characteristics such as human faces, fingerprints, irises, palm prints, finger veins, voiceprints, and gait. Among them, human face, fingerprint and iris are used in more than 80% of the global biometrics market. In the actual scenes of public security, artificial intelligence technology can be used for intelligent analysis of public security big data, realize real-time monitoring, warning, study and judgment based on the knowledge network of “people, event, places, things, and organizations”, and effectively improve the cognitive, anticipation and decision-making abilities of public security. With the technological advancement of artificial intelligence and big data, the hardware deployment of high-definition online cameras and various sensors, the gradual strengthening of public security policies such as safe cities, smart cities, and Xueliang project, as well as national strategic policies related to artificial intelligence, the intelligent applications in the public security sector will start from key regions with good conditions and will reach the whole country eventually.
Development Trends of Artificial Intelligence Industry
For potential customers in a wider range of traditional industries or offline scenarios, the practical application of artificial intelligence technology often involves the transformation of hardware equipment for specific business scenarios, software integration, as well as the deployment of local computing facilities. The research and development of actual function of algorithms and technologies should be based on deep understanding of the customers’ real business scenarios. Taking market sales as an example, the increasing market demand requires more comprehensive and timely pre-sale, sales, and after-sales services. The importance of market sales is particularly prominent when there is lack of adequate understanding of the help provided by intelligent technologies, or temporary lack of perfect scientific evaluation criteria, or there is a business scene of similar technologies. The development of artificial intelligence should not only focus on the development of cutting-edge algorithms, but also pay attention to the current commercial application and market expansion. These bring more comprehensive challenges for artificial intelligence companies which relies on high-tech talents.
Table of Content of The Full Report
1 Artificial Intelligence Industry Overview
1.1 Definition of Artificial Intelligence Industry
1.2 Development Process of Artificial Intelligence
1.3 Main Technology of Artificial Intelligence
1.4 Technical Barriers to Artificial Intelligence
1.5 Policy Environment of Artificial Intelligence
1.6 Artificial Intelligence Investment and Financing as well as Patents in China and the United States
1.7 Artificial Intelligence Industry Graph
2 Analysis of Typical Technologies of Artificial Intelligence
2.1 Intelligent Speech Recognition
2.2 Knowledge Graph
2.3 Computer Vision
2.4 Intelligent Planning and Decision Making
2.5 Automatic driving
3 Application Scenarios of Artificial Intelligence
3.1 Financial Sector
3.2 Public Security Sector
3.3 Education Sector
3.4 Pan Information Processing Sector
3.5 Healthcare sector
3.6 Industrial Manufacturing Sector
3.7 Mobile Phone and Internet Entertainment Sector
3.8 Retailing Sector
3.9 Advertising and Marketing Sector
3.10 Transportation Sector
3.11 Smart Customer Service Sector
3.12 Smart Home Sector
4 Typical Cases of Artificial Intelligence
4.1 Xiaoice 4.2 Sougou 4.3 SenseTime 4.4 Cloudwalk 4.4 Malong Technologies 4.5 Moviebook 4.6 Yi+ 4.7 Senscape 4.8 Mininglamp 4.9 Xiaoi 4.10 Turing Robot
5 The Future of Artificial Intelligence Industry