Artificial intelligence is one of the world's three cutting-edge technologies in the 21st century. It plays an irreplaceable role in social production and life. It researches and develops theories, methods, techniques and applications for simulating, extending and extending human intelligence. system. As a branch of computer science, it attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a way similar to human intelligence. It is a comprehensive new subject in which various disciplines permeate each other. It is the study of how to create artificial intelligence machines or intelligent systems to simulate the capabilities of human intelligence activities to extend the science of people's intelligence.
2) In my opinion, artificial intelligence can be divided into two parts to understand, namely "manual" and "smart". Artificial, nature is something that human resources can do, and people can complete activities. Intelligence should be understood as wisdom and ability. Since taking the road of intelligent platform, we must do two things: First, open the back-end database by opening a free API interface to developers; Second, the platform has self-learning ability, constantly improving information and enriching the database.
3) The essence of artificial intelligence is the process of machine self-learning. Machine learning consists of two major modules: one is the data source, that is, big data; the other is the data processing method, that is, the machine learning algorithm, in which the two modules run simultaneously in the self-learning process. Deep learning is a new field in machine learning research. It is mainly used to establish and simulate the neural network of human brain for analysis and learning. It mimics the mechanism of human brain to interpret data. Deep learning can enhance the ability of machine learning, and the whole mechanism has been greatly improved.
4) However, due to technical bottlenecks, artificial intelligence is far from reaching maturity. Once artificial intelligence is made, it will cause huge disruption to the existing mobile Internet product business model, and even many mobile Internet and Internet products will cease to exist. Its arrival will change the existing ways of shopping, chatting and communication, and even impact on social interaction.
5) Artificial intelligence based on big data analysis and processing can achieve accurate recommendation. However, it is used to simulate the large bottleneck of artificial, that is, it can not simulate the unique characteristics of human beings such as emotion and morality. The most fundamental solution is to change based on biological computer. This is the fundamental change that must be experienced in the evolution of artificial intelligence. The above is my view of artificial intelligence.
Intelligent robot is a very important application field and popular research direction in the field of artificial intelligence. It is directly oriented to application, with strong social benefits and rapid development. Its development requires almost all artificial intelligence technology, but also involves many other science and technology departments and fields. As an ideal research platform for artificial intelligence, it is a machine system that comprehensively simulates human beings in terms of perception, thinking, effects, etc., but its shape is not necessarily human. It is a comprehensive testing ground for artificial intelligence technology. The technology of various fields of artificial intelligence can be comprehensively examined. Its ability and level have become a manifestation and embodiment of the level of artificial intelligence technology and even the comprehensive level of human science and technology. Studying their relationship with each other can also play a part in the harmful environment to replace people engaged in dangerous work, sailing in the sky, and battlefield operations. .
2) As a third-generation robot, intelligent robots have intelligent mechanisms such as perception, recognition, reasoning, planning and learning. Among them, perception itself is the low-level intelligence of humans and animals. Intelligent robots combine intelligence and action intelligence. Its intelligence is divided into two levels: the first is the function of feeling, recognition, understanding and judgment; the second is the function of summarizing experience and learning.
3) Intelligent robot technology will develop in three directions: autonomy, intelligent communication and adaptability. Mobile function is one of the significant differences between intelligent robots and industrial robots. The life of intelligent robots lies in innovation, and research on biomimetic institutions can be inspired by many aspects such as biological institutions, mobile modes, motion mechanisms, information processing and synthesis, and perception and cognition. The development of intelligent robots will be accompanied by the emergence of intelligent algorithms. Fuzzy control, neural networks, genetic algorithms and their combination are also one of the hotspots of intelligent robot research. Due to the complexity of the working environment of the intelligent robot and the aggravation of the task, human requirements are no longer limited to a single intelligent robot. In the dynamic environment, the cooperation between multiple intelligent robots and the single robot path planning should be well unified to achieve better intelligence. Turn. Since the cost of intelligent robots is too high, it has not been popularized so far. However, one day, intelligent robots will accompany our lives and bring convenience to our lives.
Expert system is the most important and most active application field in artificial intelligence. It realizes the breakthrough of artificial intelligence from theoretical research to practical application, from general reasoning strategy discussion to application of specialized knowledge. The theory and technology of ES are constantly evolving, and the application has penetrated into almost all fields, including military, legal, commercial, computer design and manufacturing. Expert systems have been developed, many of which have been functionally achieved, even surpassing humans in the same field. The level of experts has produced enormous economic benefits in practical applications.
It is an intelligent computer system with a lot of expertise and experience, usually, mainly computer software systems. It organizes and stores in the computer the knowledge of human experts in specialized fields and the methods, experiences and know-how to solve problems. It not only simulates the thinking process of domain experts, but also enables computers to solve practical difficulties as intelligently as human experts. And complicated issues. That is, it is a system that is applied to a specialized field, has expert knowledge, can simulate expert thinking, and can reach an expert level.
ES is a simulation, extension and extension of human expert intelligence, with certain complexity and difficulty; it is a high-level intelligent assistant and effective tool that experts can trust and utilize; it can work in a specific field close to the level of human experts; it can be efficient Work accurately and quickly, without fatigue, forgetting, unaffected by the environment, emotions, etc. It breaks through the control of time and space, the program can be permanently saved, and can be copied and transmitted on the Internet; it can be carried out Effective reasoning, including various precision and inaccurate reasoning.
Compared with general computer software systems, ES is different from general computer software systems. From the nature of processing problems, ES is good at solving uncertainty, unstructured, no algorithms or algorithms, but on existing machines. The difficult problems that cannot be implemented are mainly used for knowledge information processing. From the way of dealing with problems, ES uses expert knowledge and experience to solve specialized problems instead of mathematical description methods. It is a knowledge-based intelligent problem. Solve the system; from the perspective of the structure of the system, ES flexibility and scalability are better.
ES is a copy of the wisdom of human experts. It is a kind of incarnation of human experts. It is a knowledge-based system. Although the technology is mature now, there are still many problems, such as system optimization and development, but it is these problems. The existence of the expert system will promote the development of the expert system from generation to generation.
How did artificial intelligence come from?There are some words that should indeed be subject to more doubts. Sixty years ago, some scientists set a schedule for the conference, hoping to lay the foundation for predicting and shaping the future. Their task is to use computational science to reconstruct and transcend the functioning of the human mind. The conference was named "Dartmouth Artificial Intelligence Research Project".
A draft in 1955 clearly stated the assumptions of the Dartmouth meeting: "Research is based on the assumption that every step of learning, or any other function of intelligence, can in principle be accurately described, allowing the machine to simulate "But today, the word "smart" is still very general. From autonomous vehicles to facial recognition, from chess and go to translations based on billions of samples, smarter automation solutions are fascinating. However, the words in the title of each article make us deviate from the understanding of the machine itself - machines and people are not at all, not a reflection of human intelligence.
Alan Turing published a paper on computing and intelligence in 1950, which wrote, "We can only see a short future, but we can see that there are many things to do in the future." If you want to be honest When it comes to the future, we need to know where we are going and need to accurately describe what is going on in front of us. Artificial intelligence consists of a series of emerging disciplines with more precise names: machine learning, symbolic systems, big data, supervised learning, and neural networks. However, due to the embedding of a 60-year-old analogy in its terminology, most of the discussion about them has been somewhat disrupted – and at the same time it has spawned many unhelpful fantasies.
Knowing the origins of Wikipedia doesn't necessarily help us understand why it is successful, and it doesn't necessarily teach us to use it better. But it is indeed a reminder: what we are used to today is probably not the case at first. Therefore, the future may not be what it is today.
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