Artificial intelligence technology and products have been tested in practice in the past few years, and their applications are now relatively mature, which promotes the accelerated integration of artificial intelligence and various industries. From a technical perspective, the industry widely believes that the core capabilities of artificial intelligence can be divided into three levels, namely, computational intelligence, perceptual intelligence, and cognitive intelligence.
1. Computational intelligence
Computational intelligence means that the machine has super storage capacity and super fast computing capacity, can conduct deep learning based on massive data, and use historical experience to guide the current environment. With the continuous development of computing power and the continuous upgrading of storage methods, computational intelligence can be said to have been realized. For example, AlphaGo uses enhanced learning technology to defeat the world champion of Go; e-commerce platforms conduct personalized product recommendations based on deep learning of users’ buying habits.
2. Perceived intelligence
Perceptual intelligence refers to the ability of machines to have visual, auditory, and tactile perception capabilities, which can structure unstructured data and interact with users in human communication. With the development of various technologies, the value of more unstructured data is valued and tapped, and perceptual intelligence related to perception, such as voice, image, video, and touch points, is also developing rapidly. Self-driving cars, the famous Boston dynamic robot, etc. use perceptual intelligence, which uses various sensors to perceive and process the surrounding environment to effectively guide its operation.
3. Cognitive intelligence
Compared with computational intelligence and perceptual intelligence, cognitive intelligence is more complex. It means that machines have the ability to understand, summarize, reason, and apply knowledge just like humans. At present, cognitive intelligence technology is still in the research and exploration stage. For example, in the field of public security, the feature extraction and pattern analysis of criminals’ micro and macro behaviors, the development of artificial intelligence models such as crime prediction, capital penetration, and urban crime evolution simulation System; in the financial industry, it is used to identify suspicious transactions and predict macroeconomic fluctuations. To push cognitive intelligence into the fast lane of development, there is still a long way to go.
