Comrade Xi Jinping’s important speech at the 2018 academician conference of the two academies pointed out: “The world is entering a period of economic development led by the information industry. We must grasp the opportunity of digital, network and intelligent integration development, with information and intelligence. To cultivate new kinetic energy for leverage.” This important discussion is an accurate grasp of the leading role and development of information technology in today’s world, and an important deployment for the use of information technology to promote national innovation and development.
The human society, the physical world, and the information space constitute the ternary of today’s world. The association and interaction between the three-dimensional world determines the characteristics and extent of social information. The basic way of perceiving human society and the physical world is digitization. The basic way of connecting human society and the physical world (through the information space) is networking. The way information space acts on the physical world and human society is intelligent. Digitalization, networking and intelligence are the prominent features of the new round of scientific and technological revolution and the focus of the new generation of information technology. Digitalization lays the foundation for social informationization. Its development trend is the comprehensive dataization of society. Networking provides physical carrier for information dissemination. Its development trend is the widespread adoption of information physics system (CPS); intelligentization reflects the level and level of information application. Its development trend is a new generation of artificial intelligence.
Digitization refers to the technical way of storing, transmitting, processing, processing and applying information carriers (text, pictures, images, signals, etc.) in digitally encoded form (usually binary). Digitization itself refers to the way information is represented and processed, but essentially emphasizes the computerization and automation of information applications. Dataization (data is an information carrier in the form of coding, all data is digital) In addition to digitization, it emphasizes the collection, aggregation, analysis and application of data, and strengthens the production factors and productivity functions of data. Digitization is moving from computerization to dataization, which is one of the most important trends in current social informationization.
The core connotation of dataization is the deep understanding and deep use of big data generated by the convergence of information technology revolution and economic and social activities. Big data is a fragmentary record of social economy, real world, management decision-making, etc., containing fragmented information. With the breakthrough of analytical technology and computing technology, it is possible to interpret these fragmented information, which makes big data become a new high-tech, a new type of scientific research paradigm, and a new decision-making method. Big data has profoundly changed the way of thinking and production and life of human beings, bringing unprecedented opportunities to many fields such as management innovation, industrial development and scientific discovery.
The value generation of big data has its inherent laws (subject to the principle of big data). Only by profoundly understanding and mastering these laws can we improve the consciousness and ability of consciously applying and scientifically applying big data (big data thinking). The value of big data is mainly achieved through big data technology. Big data technology is the extension and development of statistical methods, computer technology and artificial intelligence technology. It is a developing technology. The current hotspots include: blockchain technology, interoperability technology, integrated storage and management technology. Big data operating system, big data programming language and execution environment, big data foundation and core algorithm, big data machine learning technology, big data intelligent technology, visualization and human-computer interaction analysis technology, authenticity judgment and security technology. The development of big data technology relies on the resolution of some major basic problems, including: the statistical basis and computational theory of big data, the hardware and software foundation and calculation method of big data calculation, the authenticity judgment of big data inference, etc. .
Implementing the national big data strategy is an important way to advance the data revolution. Since the implementation of the national big data strategy in 2015, China’s rapid development of big data has taken shape. However, there are still some problems to be solved: the open sharing of data is lagging behind, and the data resource dividend has not been fully released; the enterprise profit model is not Stable, the integrity of the industrial chain is insufficient; the core technology has not yet made a major breakthrough, the technical level of related applications is not high; there are loopholes in security management and privacy protection, and the related system construction is still not perfect. At present, effective measures should be taken to solve the bottleneck problem that restricts the development of big data in China.
As a public infrastructure for informationization, the Internet has become the main way for people to access information, exchange information, and consume information. However, the Internet is only concerned with the interconnection between people and the resulting interconnection of services and services.
The Internet of Things is a natural extension and expansion of the Internet. It connects various objects to the Internet through information technology to help people obtain relevant information about the objects they need. The Internet of Things uses objects such as radio frequency identification, sensors, infrared sensors, video surveillance, global positioning systems, laser scanners, etc. to connect objects to the Internet through wireless sensor networks and wireless communication networks to achieve objects and objects. Real-time information exchange and communication with objects for intelligent identification, location, tracking, monitoring and management purposes. The Internet realizes the interconnection between people, services and services, while the Internet of Things realizes the interconnection between people, things and services. The core technologies of the Internet of Things include: sensor technology, wireless transmission technology, massive data analysis and processing technology, upper-layer business solutions, and security technologies. The development of the Internet of Things will go through a relatively long period of time, but it may take the lead in breakthroughs in specific areas of application. Internet of Vehicles, Industrial Internet, Unmanned Systems, and Smart Home are all areas where the Internet of Things is showing its talents.
The Internet of Things mainly solves the problem of people’s perception of the physical world. To solve the problem of manipulating physical objects, the information physical system (CPS) must be further developed. The information physics system is a multi-dimensional complex system of integrated computing, network and physical environment. It realizes real-time perception, dynamic control and information service for large engineering systems through the organic integration and deep cooperation of 3C (Computer, Communication, Control) technology. Through the human-computer interaction interface, the information physical system realizes the interaction between the computing process and the physical process, and utilizes the networked space to manipulate a physical entity in a remote, reliable, real-time, secure, and collaborative manner. Essentially, an information physics system is a network with control attributes.
Unlike the public infrastructure that provides information interaction and application, the focus of information physics development is on the development of networked physical device systems that deeply integrate sensing, computing, communication, and control capabilities. From an industry perspective, information physics systems range from smart home networks to industrial control systems to intelligent transportation systems and even national and world-class applications. More importantly, this coverage is not just a simple connection of existing equipment, but rather a multitude of devices with computing, communication, control, coordination and autonomous performance. The next generation of industry will be built on Above the information physics system. With the development and popularization of information physics system technology, physical devices that use computers and networks to expand functions will be ubiquitous, and promote the upgrading of industrial products and technologies, greatly improving automotive, aerospace, defense, industrial automation, and health. Competitiveness in major industrial sectors such as medical equipment and major infrastructure. The information physics system will not only spawn new industries, but will even reshape existing industrial layouts.
Intelligently reflects the quality attributes of information products. We say that an information product is intelligent, usually referring to the fact that this product can accomplish what a wise person can do, or has reached the level that human beings can achieve. Intelligence generally includes perception, memory and thinking skills, learning and self-adaptive ability, and behavioral decision-making ability. Therefore, intelligence can also be defined as: enabling the object to have sensitive and accurate sensing functions, correct thinking and judgment functions, adaptive learning functions, and effective execution functions.
Intelligentization is the eternal pursuit of information technology development. The main way to achieve this pursuit is to develop artificial intelligence technology. The birth of artificial intelligence technology For more than 60 years, although it has experienced three ups and downs, it has made great achievements. 1959-1976 is a stage based on artificial representation of knowledge and symbol processing, resulting in an expert system with important application value in some fields; 1976-2007 is based on statistical learning and knowledge self-representation, resulting in a variety of Neural network systems; research based on environmental self-adaptation, self-game, self-evolution, and self-learning, which has begun in recent years, is forming a new stage of artificial intelligence development—meta-learning or methodological learning, which constitutes a new generation of artificial intelligence. The new generation of artificial intelligence mainly includes big data intelligence, group intelligence, cross-media intelligence, human-machine hybrid enhanced intelligence and brain-like intelligence.
Deep learning is an outstanding representative of a new generation of artificial intelligence technology. Deep learning has become synonymous with artificial intelligence today because it surpasses human performance in many fields such as face recognition, machine translation, and chess competition. However, the deep learning topology design is difficult, the effect is difficult to expect, and the mechanism explanation is difficult. There is no solid mathematical theory to support these three major problems. Solving these challenges is the main focus of deep learning for future research. In addition, deep learning is a typical big data intelligence, and its applicability is based on the existence of a large number of training samples. Small sample learning will be the development trend of deep learning.
Meta-learning is expected to become the next breakthrough in the development of artificial intelligence. The newly developed meta-learning methods of learning, learning, learning to optimize, learning to search, learning to reason, and the excellent performance of “AlphaGo Zero” in Go show the tempting prospects of this new technology. However, meta-learning research is only the beginning, and its development faces a series of challenges.
A new wave of artificial intelligence has arrived, and the foreseeable development trend is based on big data, with model and algorithm innovation as the core, and strong computing power. The breakthrough of a new generation of artificial intelligence technology relies on the comprehensive development of other types of information technology, and also depends on the substantial progress and development of brain science and cognitive science.