The development of artificial intelligence has a history of nearly 80 years. Recently, Tesla has also said that it is not a car company, but a renewable energy company, a robotics company, and an artificial intelligence company. Tesla also made it clear that the future direction of artificial intelligence vehicles for automated driving is visual recognition + machine learning.
Since the birth of artificial intelligence, its theory and technology have become increasingly mature, and the field of application has continued to expand. Next, We will introduce you to the top10 AI technologies and related applications.
1. Problem solving
The first major achievement of artificial intelligence is the development of chess programs that can solve difficult problems. Certain techniques used in chess programs, such as looking a few steps forward, dividing difficult problems into easier sub-problems, have developed into basic artificial intelligence techniques such as search and problem reduction. Today’s computer programs can play all kinds of chess, backgammon, chess, and Go at the championship level.
In May 1997, the DeepBlue computer developed by IBM defeated the chess master Kasparov. Another problem solving program assembles various mathematical formula symbols together, and its performance reaches a very high level, and it is being applied by many scientists and engineers. Some programs can even use experience to improve their performance.
2. Logical reasoning and theorem proof
Logical reasoning is one of the most enduring sub-fields in artificial intelligence research. It is particularly important to find some ways to focus only on relevant facts in a large database, pay attention to credible proofs, and revise these proofs when new information appears. Finding a proof or a counter-evidence for the hypothetical theorem in mathematics is indeed an intelligent task.
For this, not only the ability to deduce based on assumptions, but also some intuitive skills are required. In July 1976, the author of K.Appe1 from the United States cooperated to solve a 124-year-old problem-the four-color theorem, which caused a sensation in the entire computer world. They used three large computers and spent 1,200 hours.
3. Natural language understanding
Natural language processing is one of the early research areas of artificial intelligence. Programs that can answer questions in English from internal databases have been written. These programs can translate sentences from one language to another by reading text materials and building internal databases. A language that executes instructions given in English and acquires knowledge, etc. Some programs can even translate verbal instructions input from the microphone (rather than instructions input to the computer from the keyboard) to a certain extent. Artificial intelligence has made gratifying achievements in language translation and speech understanding programs.
4. Automatic Programming
Automatic programming is an important research field of artificial intelligence. At present, computer programs that can be described for a variety of different purposes have been developed. The research on automatic programming can not only promote the development of semi-automatic software development systems, but also enable the development of artificial intelligence systems that learn by modifying their own numbers (that is, modifying their performance).
5. Expert System
Expert system is a computer program system with a large amount of specialized knowledge and experience. It uses artificial intelligence technology to reason and judge based on the knowledge and experience provided by one or more human experts in a certain field, and simulate the decision-making process of human experts to solve Those complex issues that require experts to decide.
The problems that an expert system can solve generally include interpretation, prediction, diagnosis, design, planning, monitoring, repair, guidance, and control. With the improvement of the overall level of artificial intelligence, expert systems have also been developed. In the new generation of expert systems, not only the rule-based method is adopted, but also the model-based principle is adopted.
6. Machine Learning
Learning is the main symbol of human intelligence and the basic means of acquiring knowledge. R. Shank believes: “If a computer can’t learn, it cannot be called intelligent.”
The main purpose of machine learning is to obtain knowledge from users and input data, which can help solve more problems, reduce errors, and improve the efficiency of problem solving.
7. Neural Network
The human brain is an information processing system with particularly powerful functions and an unusually complex structure. It is based on neurons and their interconnections. The study of human brain neurons and artificial neural networks may create a new generation of artificial intelligence machines.
Since the 1980s, neural network research has made significant progress. For example, Hopfield (Hopfield) proposed to use hardware to implement neural networks, Rumelhart (Rumelhart) and others proposed the back propagation (BP) algorithm in multi-layer networks.
At present, neural networks have been widely used in other fields such as pattern recognition, image processing, combination optimization, automatic control, information processing, robotics, and industrial intelligence.
8. Pattern Recognition
Pattern recognition refers to the identification of specimens imitated by a given object, such as text recognition, car license plate recognition, fingerprint recognition, voice recognition, etc. This is a perception mode that uses computers to replace or help humans. It is a simulation of human perception of the outside world, so that a computer system has the ability to simulate humans to receive outside information, recognize and understand the surrounding environment through their senses.
9. Machine Vision
Machine vision or computer vision has developed from a research field of pattern recognition to an independent subject. Vision is one of perception problems. The perception process studied in artificial intelligence usually includes a set of operations. For example, the visible scene is coded by the sensor and expressed as a matrix of gray values. These gray values are processed by the detector.
The detector searches for components of the main image, such as line segments, simple curves, and angles. These components are processed in order to infer the three-dimensional characteristic information of the scene based on the surface and shape of the scene. Machine vision has been widely used in robot assembly, satellite image processing, industrial process monitoring, aircraft tracking and guidance, and live television broadcasting.
10. Intelligent Control
Intelligent control is a type of automatic control that can independently drive intelligent machines to achieve its goals without (or as little as possible) human intervention. It is an advanced stage of automatic control. In 1965, Fu Jingsun first proposed to use artificial intelligence’s heuristic reasoning rules for learning control systems. More than ten years later, the technology to establish a practical intelligent control system has gradually matured.
Li Yanhong, chairman and CEO of Baidu, believes that artificial intelligence is a basic technology with significant industry spillover effects, which can promote changes and leapfrog development in many fields. For example: artificial intelligence can accelerate the discovery of new therapies to treat diseases and greatly reduce the cost of new drug research and development; it can drive the rapid development of emerging industries such as industrial robots and unmanned vehicles; it can greatly improve the level of national defense informatization and accelerate the development of unmanned combat equipment. application. Artificial intelligence technology will greatly enhance and expand the boundaries of human capabilities, which will have a profound impact on promoting technological innovation, enhancing national competitive advantages, and even promoting the development of human society.
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