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Narrow artificial intelligence, corresponding to the English Artificial Narrow Intelligence, referred to as ANI, is also called task-specific artificial intelligence.
Intelligent technology has been widely used to complete various specific tasks, such as intelligent driving, face recognition, AlphaGo, AI painting, natural language model, etc., which all belong to the category of intelligent technology .
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Breaking through artificial intelligence will naturally lead to higher intelligence in a specific field, but it will only be limited to that area. field. For example, there is no way for you to get an AI painting model to play Go with you, no way for a face recognition model to drive a car, and no way for you to get AlphaGo to write an article.
On the other hand, although humans only have a small brain (compared to a data center), they can do anything. Although we cannot reach expert level in every skill, it is not difficult to achieve 60 points in most things as long as we train.
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General artificial intelligence, corresponding to English Artificial General Intelligence, referred to as AGI. Unlike narrow artificial intelligence, general artificial intelligence is an artificial intelligence system with a level of intelligence equivalent to or higher than that of humans. It does not just focus on a specific field, but can understand, learn and perform a wide range of tasks.
If narrow artificial intelligence is just a relatively intelligent tool, then general artificial intelligence is a life that is no less than or even superior to humans. It can drive, draw, chat with you, and play chess with you, and it can complete every task better than humans.
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What is a cross-domain solution?
For example, we want a robot to perform fire rescue missions. After the robot enters the fire scene, it needs to make comprehensive real-time judgments based on multi-dimensional information such as fire intensity, terrain, weather conditions, burned-out conditions of buildings, physical conditions of trapped personnel, and historical experience to complete the rescue mission.
For another example, if we want artificial intelligence to create a poem, artificial intelligence needs to collect visual, auditory, olfactory, tactile and other information from the scene, and then combine it with the historical background and current humanities of the place. An unprecedented poem emerges from the environment. (It is by no means like the current big model, which involves learning a large number of existing poems to create)
Whether it is fire rescue or real poetry, it is never one or more What artificial intelligence can do in specific fields.
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