Analyze the application of artificial intelligence from the aspect of learning

When will machines be able to think, work, and learn like humans? This is a puzzle that has been studied by the scientific and technological community for decades. In the past two years, with the launch of applications such as Apple Siri and Microsoft Xiaoice, artificial intelligence has become closer and closer to our lives.

Yesterday, on topics related to artificial intelligence, the reporter interviewed Dr. Rui Yong, vice president of Microsoft Research Asia.

Microsoft's Artificial Intelligence Direction: Tall.

Rui Yong: The development of perception technology, intelligent analysis and learning technology, and big data technology has made artificial intelligence develop by leaps and bounds. One of the important reasons for Microsoft's 30% growth last year is its focus on developing AI products and services.

Our philosophy is "do more, know more, be more", and I have an unofficial personal translation called Gao Dashang, which is high efficiency, great wisdom, and high taste.

Microsoft recently launched the "Cortana" and "Xiaoice" software applications. Cortana is like a personal secretary, arranging your itinerary, coordinating time, telling you about traffic conditions, and providing you with feasible plans. Xiaoice is like a friend, chatting with you like a real person.

Some users on Weibo said that chatting with Xiaoice even produces feelings. Xiaoice's artificial intelligence comes from machine learning, and the computer will have its own wisdom after tens of millions of learnings.

Great wisdom focuses more on the construction of intelligent transportation and smart cities. For example, we have launched a fine-grained air quality map of cities such as Beijing and Shanghai, which can display air quality data on each square kilometer in real time by integrating real-time data, traffic conditions, people flow and many other factors, and even the air quality status of a certain area in the future for a period of time.

It's even more interesting to be in good taste. Microsoft Research Asia has recently developed a technology that allows you to create a very realistic 3D model of your hair by drawing two strokes on a 2D hairstyle** that follows the trend of your hair, with a clear direction and texture of your hair. This technique may seem inconspicuous, but it is also very useful, you can change the hairstyle of the character at will in animations and movies, and you can also put it in the barber shop, so that people can choose the hairstyle they want in advance.

There's still a long way to go from functional to intelligent.

Chinese artificial intelligence is developing rapidly, and ** attaches great importance to artificial intelligence. The professional direction of artificial intelligence has scientific research, engineering development, computer direction, software engineering, applied mathematics, electrical automation, communications, machinery manufacturing, although the prospect of artificial intelligence is very good, but its difficulty coefficient is very high, the current demand for artificial intelligence talents is very large, compared with other technical positions, the degree of competition is reduced, and the salary is relatively high, therefore, now is a good time to enter the field of artificial intelligence. The development prospects of artificial intelligence are still very good, for several reasons, intelligence is one of the important trends in the future.

1. The development of the industrial Internet will inevitably lead to the development of artificial intelligence, and artificial intelligence technology will become one of the essential skills for people in the workplace.

At present, artificial intelligence has received extensive attention in the field of computing, and I believe that the application prospects will be more extensive in the future.

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The application of AI technology in learning is as follows:

1. Mining and intelligent analysis of educational data.

Educational data mining is a comprehensive use of mathematical statistics, machine learning, data mining and other technologies and methods to process and analyze educational big data. Through data modeling, the correlation between learners' learning results and learning content, learning resources, teaching behaviors and other variables is discovered, so as to determine the future learning trend of learners.

2. The early education machine violently blinds the Jane people.

In recent years, intelligent service robots have gradually penetrated into all aspects of human life, and they are not only the best human companions and production tools, but also have gradually become reliable "family members". With the current prevalence of the children's economy, the proportion of children's education industry consumption in the overall household consumption is gradually increasing.

Intelligent early education robots have replaced traditional electronic education products to become the mainstream of family early childhood education products in the future, which can not only accompany children, but also guide children to learn.

3. Artificial intelligence can play a very important role in the evaluation of the learning process.

He can analyze your mastery of knowledge in the learning process, the subject ability of each knowledge point, your core literacy, and the development of your physical health and mental health. It can make our educational evaluation from a single subject knowledge evaluation to a comprehensive and comprehensive evaluation; It can change our evaluation from a final exam to a process evaluation.

First: Start with the basics. Research in the field of artificial intelligence is concentrated in six areas: natural language processing, machine learning, computer vision, knowledge representation, automatic reasoning, and robotics.

One of the core problems of artificial intelligence is mathematical problems, and more specifically, the design of algorithms, and the specific implementation of algorithms involves computer knowledge. Therefore, among the many disciplines involved in artificial intelligence (philosophy, mathematics, computing, neurology, economics, linguistics, etc.), mathematics and computer fundamentals are very critical for R&D personnel.

Second, understand the R&D content and R&D methods of artificial intelligence. Although the research and development of artificial intelligence has gone through more than 60 years, it is still in the early stage of the development of the industry, and machine learning, computer vision and robotics are relatively popular fields.

Before learning these specific knowledge, there should first be an overall cognitive process of artificial intelligence, and it is a good way to understand the development history of artificial intelligence.

Third: start with big data. For people with a weak foundation, it is a more realistic path to enter the field of artificial intelligence through big data.

Big data technology has matured and is currently in the initial stage of application, and big data, as an important foundation of artificial intelligence, will play a greater role in promoting the development of artificial intelligence in the future. As one of the important means of data analysis, machine learning is currently widely used in the field of big data, so it is a good route to enter the field of artificial intelligence through big data into machine learning.

There is still a lot of knowledge you need to master to get started with artificial intelligence, including: natural language processing, machine learning, computer vision, automatic reasoning, and robotics. Although each of these areas has a different focus, they all require an important foundation, which is the foundation of mathematics and computing.

One of the core problems of artificial intelligence is mathematical problems, so only people who are good at mathematics can learn artificial intelligence knowledge well.

The main needs of the artificial intelligence major are: "Artificial Intelligence, Society and Humanities", "Philosophical Foundations and Ethics of Artificial Intelligence", "Advanced Robot Control", "Cognitive Robots", "Robot Planning and Learning", "Bionic Robots", "Swarm Intelligence and Autonomous Systems", "Unmanned Technology and System Implementation", "Game Design and Development", "Computer Graphics", "Virtual Reality and Augmented Reality", "Modern Methods of Artificial Intelligence I".

The main fields of artificial intelligence are: machine learning, introduction to artificial intelligence (search method, etc.), image recognition, biological evolutionary theory, natural language processing, semantic web, game theory, etc. The prerequisite courses are signal processing, linear algebra, calculus, and programming (preferably with a foundation in data structures).

Foundation in mathematics required: Advanced Mathematics, Linear Algebra, Probability Theory, Mathematical Statistics and Stochastic Processes, Discrete Mathematics, Numerical Analysis. Accumulation of algorithms is required:

Artificial neural networks, support vector machines, genetic algorithms, etc.; Of course, there are algorithms needed in various fields, such as SLAM needs to be studied to allow robots to navigate and map the location environment by themselves;

Generally, you need to learn network interconnection technology, Linux operating system, C language programming, MySQL database management and application, web front-end development, introduction to artificial intelligence, Pyhton introduction and improvement, Python core programming.

A foundation in mathematics is required:

Advanced Mathematics, Linear Algebra, Probability Theory, Mathematical Statistics and Stochastic Processes, Discrete Mathematics, Numerical Analysis.

Accumulation of algorithms is required:

Artificial neural networks, support vector machines, genetic algorithms, etc.; Of course, there are algorithms needed in various fields, such as SLAM needs to be studied to allow robots to navigate and map the location environment by themselves; In short, there are many algorithms, which take time to accumulate.

It is necessary to master at least one programming language, after all, the implementation of algorithms still needs to be programmed; If you go deep into hardware, some basic electrical courses are essential.

At present, some colleges and universities have opened artificial intelligence majors at the undergraduate level, which are mainly divided into four parts from the perspective of curriculum architecture, the first part is the basic discipline part, which mainly involves mathematics and physics-related courses; The second part is the basic computer course, which involves programming language, operating system, algorithm design and other courses; The third part is the basic course of artificial intelligence, which involves the foundation of artificial intelligence, machine learning, cybernetics, neuroscience, linguistics and other contents. The fourth part deals with knowledge of AI platforms.

Since artificial intelligence is a typical interdisciplinary discipline, there is still a relatively large amount of content to be learned in artificial intelligence majors, and the learning difficulty is relatively large, so if you choose an artificial intelligence major at the undergraduate level, you need to have strong learning ability. Because the learning process of artificial intelligence majors has high requirements for the learning environment, colleges and universities that offer artificial intelligence majors often have special data centers and computing centers to provide students with data and computing support.

At present, there are six major research directions of artificial intelligence, involving computer vision, natural language processing, robotics, automatic reasoning, machine learning and knowledge representation, and there is a close relationship between these research directions. Since different universities often have different resource integration capabilities and have a certain focus in the field of artificial intelligence, when choosing a specific learning direction, we should try to choose a direction with strong discipline strength based on the actual situation of the university where we are located, so that we will have a better learning experience.

The relationship between AI and learning is as follows:

1. Artificial intelligence is a kind of design thinking for machine thinking and behavior, which aims to realize the automatic operation of computer systems by imitating human intelligent behavior in complex situations. Learning limb learning is a method of artificial intelligence that uses deep neural networks to simulate various complex functions of the human brain, so as to achieve automatic operation.

2. Learning is one of the important technical means to realize artificial intelligence, especially in the fields of computer vision and natural language processing. However, learning is not the only way to make AI a reality, and there are many other technologies and algorithms that play an important role in different fields.

Extension of the basic definition of artificial intelligence:

Artificial intelligence is abbreviated as AI. It is a new technical science that researches and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

Artificial intelligence is a key branch of computer science that seeks to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a similar way to human intelligence, including robotics, language recognition, image recognition, natural language processing, and expert systems.

Artificial intelligence is an extremely challenging science, and those who do it must be computer literate, psychological, and philosophical. Artificial intelligence is a very broad science, which consists of different fields, such as machine learning, computer vision, etc.

Artificial intelligence is currently a fast-growing field, with a high demand for talent, low competition and relatively high salaries compared to other technical positions, so now is a good time to enter the field of artificial intelligence. Research also shows that people with more than three skills are more attractive to businesses, and the trend is becoming more obvious, so IT technicians need to master more skills while mastering a technology!