The computer programs used in the field of artificial intelligence (AI) are highly specialized. They can perform tasks such as fly airplanes, play chess or assemble cars in controlled industrial environments.
These are examples of Narrow Intelligence, which is focused on performing narrow tasks.
These traditional AI programs lack the versatility and adaptability of human intelligence. For example, they cannot come into a new home and cook, clean and do laundry, reports ScienceDaily.
A research team from Gothenburg, Sweden has created an AI program that can learn how to solve problems in many different areas. The program was designed to imitate certain aspects of children's cognitive development.
Artificial general intelligence (AGI), is a field where scientists try to create computer programs with a generalized type of intelligence. This would enable programs to instruct machines to cook, clean and do laundry.
"We have developed a program that can learn for example basic arithmetic, logic and grammar without any pre-existing knowledge," says Claes Strannegård, a member of the research team together with Abdul Rahim Nizamani and Ulf Persson.
The best example of general intelligence that we know of today is the human brain, and the scientist's strategy has been to imitate, at a very fundamental level, how children develop intelligence.
Children can learn a wide range of things. They build new knowledge based on previous knowledge and they can use their total knowledge to draw new conclusions. This is exactly what the scientists wanted their program to be able to do.
"We postulate that children learn everything based on experiences and that they are always looking for general patterns," says Strannegård.
The child can in this way create a large number of patterns not only in mathematics but also in other areas, such as logic and grammar. The patterns in a certain area can then be combined with each other and make it possible to solve entirely new problems.
The program developed by the Gothenburg scientists works in a similar manner. It can identify patterns by itself and therefore differs from programs where a programmer has to formulate which rules the program should apply, according to ScienceDaily.
"We are hoping that this type of program will eventually be useful in several different practical applications. Personally, I think a versatile household robot would be tremendously valuable, but we're not there yet," says Strannegård.
