Artificial Intelligence in the Future: Towards Truly Intelligent Machines
This article includes some thoughts about artificial intelligence (AI). First, a difference is drawn between strong and weak AI, as well as the associated notions of general and particular AI, demonstrating that all extant AI manifestations are weak and specialised. The main current models are briefly presented, emphasising the relevance of corporality as a vital factor in achieving universal AI. The importance of providing common-sense information to machines is also emphasised in order to progress toward the lofty goal of developing general AI. lately, he also mentioned the existing limitations with this AI technique.
The ultimate aim of artificial intelligence (AI) is for a machine to have general intellect similar to that of a person. This is one of the most ambitious scientific goals ever suggested. It is equivalent in difficulty to other major scientific aims like understanding the genesis of life or the Universe, or finding the structure of matter. This desire in creating intelligent devices has led to the creation of models or metaphors of the human brain in previous ages. Descartes, for example, pondered in the seventeenth century if a complicated mechanical system of gears, pulleys, and tubes could potentially imitate mind.
The hypothesis of the physical symbol system: weak ai vs. strong ai
In actuality, computers utilise digital electrical circuits to produce symbols, whereas individuals employ neural networks. According to the PSS hypothesis, the type of underlying layer (electronic circuits or neural networks) is irrelevant as long as symbols can be processed. Remember that this is a hypothesis that should not be accepted or rejected only on the basis of its merits. In every instance, experimental testing must be done to verify the validity or rejection of the scientific process.
AI
is the branch of science dedicated to testing this theory in the context of
digital computers, i.e., determining if a properly programmed computer is
capable of general intelligent behaviour.
It's
crucial to specify that this must be general intelligence, not particular
intelligence, because human intellect is likewise general. It's another thing
entirely to demonstrate specialised intellect. Computer systems capable of
playing Grand-Master chess, for example, are incapable of playing checkers,
which is a far simpler game. A separate, independent software must be written
and executed in order for the same computer to play checkers.
To put it another way, the computer can't adapt to the game of checkers by using its chess skills. Humans, on the other hand, may use their chess knowledge to play checkers flawlessly in minutes. Weak AI, as opposed to strong AI, is concerned with the creation and deployment of artificial intelligences that can only act intelligently in a limited number of situations.
The latter is
referred to by Newell, Simon, and the other AI pioneers. The PSS theory was
formally proposed in 1975, although it was implied in the 1950s thinking of AI
pioneers, including Alan Turing.
This difference between weak and strong AI was initially made by philosopher John Searle in an article critiquing AI in 1980 (Searle, 1980), which sparked a lot of debate at the time and continues to do so now. Strong AI would indicate that a well-designed computer is capable of intellect comparable to, if not superior to, that of humans. Searle attempted to show in his paper that strong AI is impossible, and it is important to note that broad AI is not the same as strong AI.
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