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Weak artificial intelligence (weak AI) is artificial intelligence that implements a limited part of the mind, or, as Artificial Narrow Intelligence, [1] [2] [3] is focused on one narrow task. Weak AI is contrasted with strong AI , which can be interpreted in various ways:
Weak AI hypothesis: An artificial intelligence system can (only) act like it thinks and has a mind and consciousness. The first one he called "strong" because it makes a stronger statement: it assumes something special has happened to the machine that goes beyond those abilities that we can test.
Moravec's paradox is the observation in the fields of artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational resources.
This problem is often discussed through the contrast between weak and strong artificial intelligence. Weak or narrow artificial intelligence is limited to specific mental capacities or functions. It focuses on a particular task or a narrow set of tasks, like autonomous driving, speech recognition, or theorem proving.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Weak artificial intelligence → – the term "Weak artificial intelligence" is ambiguous and confusing, contrary to the term "Narrow artificial intelligence", which is basically AI designed for a narrow range of tasks. This is also most of what the article is about, although we could keep a section covering the term "Weak AI".
It is discussed in artificial intelligence research publications as an approach to strong AI (artificial general intelligence) and to at least weak superintelligence. Another approach is seed AI, which would not be based on existing brains. Computer-based intelligence such as an upload could think much faster than a biological human even if it ...
In 1960, AI pioneer Norbert Wiener described the AI alignment problem as follows: . If we use, to achieve our purposes, a mechanical agency with whose operation we cannot interfere effectively ... we had better be quite sure that the purpose put into the machine is the purpose which we really desire.
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