Main Applications and Basic Principles of Artificial Intelligence Technology

1: What is artificial intelligence?

Artificial intelligence (AI) is a new technological science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. It is a process of cognition, decision-making and feedback. Artificial Intelligence Master Energy (AI) is a subject used to study the computer to simulate some human thinking process and intelligent behavior (such as learning, reasoning, thinking, planning, etc.). It mainly includes the principle of computer to realize intelligence, making similar computers of human brain intelligence, so that the computer can achieve a higher level of application.

2: Research Value of Artificial Intelligence

For example, the heavy scientific and engineering calculation is supposed to be undertaken by the human brain. Nowadays, the computer can not only complete this calculation, but also do it better, faster and more accurately than the human brain. Therefore, the contemporary people no longer regard this calculation as a "complex task that needs artificial intelligence to complete". It can be seen that the definition of complex work changes with the development of the times and the progress of technology. The specific goal of artificial intelligence is naturally developing with the changes of the times. On the one hand, it keeps gaining new development, on the other hand, it turns to more meaningful and difficult goals.

3: What are the sub-domains of AI?

The application fields of AI technology include in-depth learning, computer vision, intelligent robots, virtual personal assistants, natural language processing-speech recognition, natural language processing-general, real-time speech translation, context-aware computing, gesture control, automatic visual content recognition, recommendation engine, etc.

(1): Deep learning

As an application branch in the field of artificial intelligence, in-depth learning is an important application field in terms of both the number of companies on the market and the investment preferences of investors. Speaking of in-depth learning, we must first think of AlphaGo. Through learning and updating algorithms over and over again, we finally defeated Go master Li Shishi in the man-machine war. Baidu's robot "Xiaodu" has participated in the "man-machine war" of the strongest brain many times and won the victory, which is also the result of deep learning. _

Technical principles of in-depth learning:

1. Construct a network and randomly initialize the weights of all connections;

2. Export a large amount of data to the network;

3. The network processes these actions and learns them.

4. If the action meets the specified action, the weight will be increased, and if not, the weight will be reduced.

5. The system adjusts the weight through the above process;

6. After thousands of studies, it surpasses human performance.

(2): Computer vision

Computer vision refers to the ability of computer to recognize objects, scenes and activities from images. Computer vision has a wide range of applications, including medical imaging analysis, which is used to improve the prediction, diagnosis and treatment of diseases. Face recognition is automatically recognized by Alipay or some self help services on the Internet. At the same time, in the field of security and monitoring, there are many applications...

Technical Principles of Computer Vision:

Computer vision technology uses a sequence of image processing operations and other technologies to decompose image analysis tasks into manageable chunks. For example, some techniques can detect edges and textures of objects from images. Classification techniques can be used to determine whether the identified features can represent a class of objects known to the system.

(3) Speech recognition:

Speech recognition technology is the most popular and easy-to-understand way of speaking is to convert speech into text, and recognize and process it. The main applications of speech recognition include medical dictation, voice writing, computer system voice control, telephone customer service and so on.

Principles of speech recognition technology:

1. Processing the sound, using the moving window function to frame the sound;

2. After the sound is subdivided into frames, it becomes many waveforms, so it is necessary to extract the acoustic signs of the waveforms into states.

3. After feature extraction, sound becomes a matrix of N rows and N columns. Then the phonemes are combined into words.

(4) Engine recommendation:

I don't know if you have the experience of surfing the Internet now, that is, the website will push you some relevant website content according to the pages you have visited and the keywords you have searched before. This is actually a manifestation of engine recommendation technology. Why does Google do the free search engine is to collect a large number of natural search data, enrich its big data database, and prepare for the artificial intelligence database in the future.

Engine Recommendation Technology Principle:

Recommendation engine is based on users'behavior and attributes (data generated by users browsing websites). Through algorithm analysis and processing, it actively discovers users' current or potential needs, and actively pushes information to users'information network. Quick recommendation to users to improve browsing efficiency and conversion rate.

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Author: Leikun 153

Source: CSDN

Original: https://blog.csdn.net/leikun153/article/details/79365212

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