Artificial intelligence industry map and major breakthrough inventory

According to Sage, the adstrary of artificial intelligence will boost global GDP by an additional 14% by 2030, equivalent to $15.7 trillion in growth.
more and more governments and business organizations around the world are realizing the economic and strategic importance of AI and dabbling in ai AI in national strategies and business activities.
the global AI market will experience a phenomenar growth in the coming years.
2020, China's artificial intelligence industry from the application to the bottom of innovation have made a major breakthrough, the industrial chain of all links continue to improve, the industry's ability to resist risks further strengthened, and some links reached the international leading level.
, the artificial intelligence industry map view of the artificial intelligence industry chain can be divided into upstream basic layer, midstream technology layer and downstream application layer three links.
Among them, the basic layer is the foundation of the artificial intelligence industry, mainly the research and development of hardware and software, such as AI chip, data resources, cloud computing platform, etc., to provide data and computing support for artificial intelligence; Machine learning), development platforms (basic open source frameworks, technology open platforms) and application technologies (computer vision, machine vision, intelligent voice, natural language understanding);
is to form a hardware and software product or solution by integrating one or more types of AI basic application technologies for specific application needs.
table 1: Artificial intelligence industry chain and sub-industry source: Firestone creation according to public information finishing II, China's artificial intelligence industry in general, China's artificial intelligence industry presents upstream to seek a breakthrough;
and in the process of industrial development of domestic market advantages, data advantages, talent advantages continue to appear.
(1) chip is the heart chip of artificial intelligence is the heart of the artificial intelligence industry.
foundation layer is the foundation of artificial intelligence industry, mainly research and development hardware and software, such as AI chips, data resources, cloud computing platform, etc., to provide data and computing support for artificial intelligence.
include computing hardware (AI chips), computing system technology (big data, cloud computing, and 5G communications), and data (data acquisition, labeling, and analysis).
chip industry is particularly critical, is the heart of the artificial intelligence industry.
, China's artificial intelligence chip industry is in its infancy, in recent years, China's chip design industry market has been expanding.
2019, sales in China's chip design industry grew to 306.4 billion yuan, up 21.6% year-on-year, according to the China Semiconductor Industry Association.
with the continuous development of electronic devices to intelligent, miniaturized direction, chip integration, density and performance of the increasing, China's packaging model continues to develop new, the industrial scale shows rapid growth.
data show that in 2019, China's package testing scale increased to 235 billion yuan.
a new study released by Compass Intelligence, a market research consultancy, in 2018 shows that the top three companies in the world's top A_List 15 artificial intelligence (AI) chip companies are Nvidia, Intel and NXP, with Apple at 8th, Samsung at 11th and Huawei at 12th.
As the cornerstone and heart of the artificial intelligence industry, the position of chip in the industry is unquestionably unshakable, but the overall design level of China's chip industry is larger than that of foreign countries, especially in chip production there is a serious neck phenomenon.
current domestic chip manufacturers typical enterprises include Huawei Heath, Camsan, Horizon, Ali Pingtou and so on.
(2) data is the blood data of artificial intelligence industry is one of the main driving force of artificial intelligence industry, and the huge amount of data resources is also one of the differentiated advantages of developing artificial intelligence industry in China.
report by IDC, an international data company, and Seagate, a data storage company, shows that by 2025, as new technologies such as the Internet of Things in China continue to advance, they will produce more data than the United States.
the amount of data generated in China will increase from about 7.6ZB in 2018 to 48.6ZB in 2025, according to Guiyang Big Data Exchange, China's large data industry market will continue to grow at a high rate over the next five years.
With the development of 5G and internet of things, the industry's demand for more efficient and green data centers and cloud computing infrastructure is increasing, the big data base layer continues to maintain high growth, the overall size is expected to reach 667.02 billion yuan in 2020, by 2022 will exceed trillion yuan, continue to promote the transformation and upgrading of traditional industries, stimulate economic growth vitality, and help new smart cities and digital economic construction.
of data sharing, convergence and transactions at this stage will continue to grow with the depth of the big data and artificial intelligence industries on the application side.
(3) Ai AI industry applications in the world leading China's huge population advantages and market demand, in the leading enterprises and capital driven by China's artificial intelligence industry application-side product development world-leading, resulting in a large number of popular products, including smart cars, robots, smart home, wearable devices.
Smart cars include intelligent networking technology, driverless technology, robots are divided into industrial robots and special robots (service robots, underwater robots, entertainment robots, military robots, agricultural robots);
3. In February 2020, Ali Group, in cooperation with Zhejiang Shulan Hospital, where Li Lanxuan is located, carried out research work on new coronavirus drugs around the development of rapid Cryo-EM 3D imaging technology based on deep learning, the fusion of topology and geometric characteristics of deep neural networks for ligate-protein prediction, protein structure prediction based on deep learning, and the use of protein sequence prediction for protein 3D structure.
during the outbreak, Ali offered free AI to public research institutions around the world to speed up the development of new drugs and vaccines for pneumonia.
In February 2020, the National Development and Reform Commission, the Ministry of Industry and Information Technology, the Ministry of Science and Technology and other 11 ministries jointly sealed the official release of the "Smart Car Innovation Development Strategy" proposed that by 2025, the realization of conditional self-driving intelligent cars to achieve large-scale production, to achieve a high degree of self-driving intelligent cars in a specific environment of market-oriented applications.
Smart transportation system and smart city-related facilities construction has made positive progress, vehicle wireless communication network (LTE-V2X, etc.) to achieve regional coverage, the new generation of vehicle wireless communication network (5G-V2X) in some cities, highways gradually carry out applications, high-precision space-time benchmark service network to achieve full coverage.
2020, the CPC Central Committee and the State Council issued opinions on building a more perfect system of market-oriented allocation of factors.
proposed to enhance the value of social data resources.
foster new industries, new business patterns and new models of digital economy, and support the construction of standardized data development and utilization scenarios in agriculture, industry, transportation, education, security, urban management, public resources trading and other fields.
the role of trade association chamber of commerce to promote artificial intelligence, wearables, car networking, Internet of Things and other areas of data collection standardization.
In June 2020, Liu Yunjie, a member of the Chinese Academy of Engineering, said that Nanjing Network Communications and Security Zijinshan Laboratory had developed a CMOS mmWale fully integrated 4-channel phased array chip and completed chip packaging and testing, reducing the cost per channel from 1000 yuan to 20 yuan.
large-scale active antenna array with a 1024-channel antenna unit integrated in the package, and the chip and antenna array is expected to be available for 5G systems in 2022.
June 2020, the State Drug Administration announced that the intracranial tumor magnetic resonance imaging-assisted diagnostic software of BioMind" under Ander Medical Intelligence has passed the approval of NMPA three types of medical devices.
the product was developed by the "Artificial Intelligence Research Center for Neuropathy" jointly established by Tiantan Hospital and Ander Medical Intelligence, and is the first medical AI software approved by the Drug Administration under the name "Image Assisted Diagnostics".
In August 2020, in order to strengthen the standardized top-level design in the field of artificial intelligence, promote research and development of artificial intelligence industry technology and standard-setting, and promote the healthy and sustainable development of the industry, the National Standardization Management Committee, the Central Network Information Office, the National Development and Reform Commission, the Ministry of Science and Technology, the Ministry of Industry and Information Technology jointly issued the Guidelines for the Construction of the National New Generation artificial intelligence standard system.
According to the Guide to the Construction of the National New Generation Artificial Intelligence Standard System, by 2021, we will clarify the top-level design of artificial intelligence standardization, study the overall rules of standard system construction and standard development, clarify the relationship between standards, guide the orderly development of ai AI standardization work, and complete the pre-research work on more than 20 key standards, such as key common technologies, key areas of technology and ethics.
In October 2020, the unmanned bus jointly deployed by China Mobile and Light Boat Zhihang landed in Suzhou High-speed Railway New City, and launched the Suzhou Unmanned Bus Early Bird Program, which recruits a group of citizens with daily commuting needs to take it free of charge.
December 2020, the University of Science and Technology of China announced that its Pan Jianwei team, in collaboration with the Shanghai Institute of Microsysmics of the Chinese Academy of Sciences and the National Parallel Computer Engineering Technology Research Center, had successfully constructed the "Nine Chapters" of the quantum computing prototype of 76 photons.
based on existing theories, in the classical mathematical algorithm "Gaussian Bose Sampling" task, "nine chapters" one minute to complete the task, supercomputers take 100 million years.
December 2020, Microsoft Asia Research Announced the establishment of OpenNetLab Open Network Platform Alliance in a number of Asian universities, including Tsinghua University, Peking University, Nanjing University, Lanzhou University, National University of Singapore and Seoul National University.
OpenNetLab platform aims to drive the application and development of artificial intelligence (AI) in network research and build a healthy and sustainable network research ecosystem by providing researchers with a common distributed network test platform and real network evaluation data sets.
, the platform has completed the construction of multiple nodes and small-scale deployment testing, and is gradually entering the large-scale testing phase.
December 2020, the Network and Media Lab, led by Professor Wenwu Zhu of Tsinghua University, released the world's first open source autograph learning kit, Auto Graph Learning.
the tool supports fully automated machine learning on graph data, and supports two of the most common tasks in graph machine learning: node classification tasks and graph classification tasks.