What are the five categories of artificial intelligence?

Artificial intelligence technology includes computer vision, speech recognition, natural language processing, machine learning and big data.

1, computer vision

Computer vision of artificial intelligence is a science that studies how to make machines "see". It uses cameras and computers to identify, track and measure targets instead of human eyes, and further processes the graphics, so that computers can process images more suitable for human eyes to observe or send them to instruments for detection. From the perspective of artificial intelligence, computer vision should give machines the intelligence of "seeing", which is similar to the intelligence of "listening" given by speech recognition. Both of them belong to the category of perceptual intelligence.

2. Speech recognition

Speech recognition needs preprocessing, feature extraction, acoustic model training, language model training, speech decoding and other processes. Pretreatment is the digital processing of sound, including sampling, quantization, pre-emphasis and other operations. Feature extraction is to extract the features of the processed speech, and extract the information reflecting the speech features, such as sound spectrum, sound vector and so on.

3. Natural language processing

Natural Language Processing (NLP) is an important direction in the field of artificial intelligence, which focuses on various theories and methods of effective communication between people and computers using natural language. NLP research involves natural language, that is, the language people use every day. The goal is to develop a computer system, especially a software system, which can effectively realize natural language communication.

4. Machine learning

Machine learning is an interdisciplinary field, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and many other disciplines. It uses computer technology to calculate and analyze the collected data, and constantly improves the calculation method to improve the accuracy of completing a specific system. Machine learning inputs data into a learning algorithm, and the learning algorithm generates a calculation model according to the input data, and then inputs another set of test data into the model, and the model can output judgment results.

5. Big data

Both artificial intelligence and big data involve data processing and analysis, but the emphasis and purpose are different. Artificial intelligence aims to solve various problems through data-driven algorithms, including image recognition, speech recognition, natural language processing and so on. To achieve machine intelligence. Big data focuses on the analysis and mining of large-scale data to discover its laws and values, thus providing decision support for enterprises or organizations.

The development of artificial intelligence:

In the golden age of AI, artificial intelligence was widely used in different fields, such as machine translation, natural language processing, computer vision and so on. During this period, some famous AI projects appeared, such as Stanford Cart and Shakey. However, in the 1970s, artificial intelligence suffered its first trough, mainly because some projects failed and funds became tight.

In the period when AI flourished again, artificial intelligence was further developed and applied. During this period, some new artificial intelligence schemes appeared, such as neural network and genetic algorithm. These new schemes provide a new direction for the application and development of artificial intelligence.

Since 1990s, artificial intelligence has been widely used, such as intelligent manufacturing, intelligent transportation and intelligent agriculture. At the same time, artificial intelligence algorithms are constantly optimized and developed, such as the application of deep learning algorithms in image recognition, natural language processing and other fields. The development of these application fields has brought more innovations and opportunities for artificial intelligence.