What are the development stages of artificial intelligence?

The development of artificial intelligence can be divided into the following stages:

Rule mode stage: The origin of artificial intelligence can be traced back to 1950s, when rule mode was mainly adopted, also known as logical reasoning mode. This method mainly realizes the application of artificial intelligence by designing expert system and knowledge map.

Statistical learning stage: In 1980s, artificial intelligence methods based on statistical learning theory appeared, such as support vector machine, decision tree and random forest. These algorithms mainly realize tasks by analyzing data and pattern recognition, such as image recognition and speech recognition.

Deep learning stage: With the continuous improvement of computer performance and the development of neural network, deep learning technology has gradually become the mainstream technology in the field of artificial intelligence. Deep learning mainly completes tasks such as image recognition and natural language processing through multi-level neural networks, and usually requires a lot of data and computing resources to train and optimize models.

Self-learning stage: At present, the development of artificial intelligence has entered the self-learning stage, and the machine can continuously improve its ability and performance by accumulating and learning its own experience. At the same time, the integration of artificial intelligence and other technologies is also constantly strengthening, such as the Internet of Things, big data, cloud computing and so on. The combination of these technologies enables artificial intelligence to be applied in more scenes.

To sum up, the development of artificial intelligence has gone through the stages of rule mode, statistical learning, deep learning and self-learning. With the development of technology and the expansion of application scenarios, artificial intelligence will be more widely used and innovated in the future.