What are the main application fields of AI technology?

With the emergence and popularization of intelligent household appliances, wearing devices, intelligent robots and other products, artificial intelligence technology has entered all areas of life, causing more and more attention. So, in which fields are AI currently applied and what technical principles are applied?

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.

Many people used to joke that AI is like a train. You look forward to it. It finally comes, and then it whistles past, leaving you behind. Although this is a joke, it also reflects the rapid development and unimaginable speed of AI technology. You may be left behind by carelessness.

What are the subdivisions of AI technology?

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.

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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 conforms to 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...

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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.

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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. It is necessary to extract the acoustic signs from the waveforms and turn them into states.

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

4. Virtual Personal Assistant

When it comes to virtual personal assistants, you may not have a specific concept in mind. But when it comes to Siri, you're sure to immediately understand what virtual personal assistants are. In addition to Siri, Windows 10 Cortana is also a typical example.

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Principles of Virtual Personal Assistant Technology: (Take Siri as an example)

1. After the user speaks to Siri, the voice will be coded immediately and converted into a compressed digital file which contains the relevant information of the user's voice.

2. Because the user's mobile phone is on, the voice signal will be transferred to the base station of the mobile operator used by the user, and then sent to the user's Internet Service Provider (ISP) through a series of fixed wires. The ISP has a cloud computing server.

3. The built-in series of modules in the server will identify what the user has just said through technical means.

In a word, the working principle of virtual assistant software such as Siri is "Local Speech Recognition + Cloud Computing Service".


5. Language Processing

Natural Language Processing (NPL), like computer vision technology, integrates a variety of technologies that are helpful to achieve goals, and achieves natural language communication between human and computer.

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Principles of Language Processing Technology:

1. Lexical analysis of Chinese character coding;

2. Syntactic analysis;

3. Semantic analysis;

4. Text generation;

5. Speech recognition;

6. Intelligent Robot

Intelligent robots can be seen everywhere in life, sweeping robots, accompanying robots... These robots can not do without the support of artificial intelligence technology, whether they are chatting with human voice, autonomous positioning, navigation, walking, security monitoring and so on.

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Read the Chinese version for details.