Strong AI aims to build machines whose overall intellectual ability is indistinguishable from that of a human being. Joseph Weizenbaum, of the MIT AI Laboratory, has described the ultimate goal of strong AI as being "nothing less than to build a machine on the model of man, a robot that is to have its childhood, to learn language as a child does, to gain its knowledge of the world by sensing the world through its own organs, and ultimately to contemplate the whole domain of human thought". The term "strong AI", now in wide use, was introduced for this category of AI research in 1980 by the philosopher John Searle, of the University of California at Berkeley. Some believe that work in strong AI will eventually lead to computers whose intelligence greatly exceeds that of human beings. Edward Fredkin, also of MIT AI Lab, has suggested that such machines "might keep us as pets". Strong AI has caught the attention of the media, but by no means all AI researchers view strong AI as worth pursuing. Excessive optimism in the 1950s and 1960s concerning strong AI has given way to an appreciation of the extreme difficulty of the problem, which is possibly the hardest that science has ever undertaken. To date, progress has been meagre. Some critics doubt whether research in the next few decades will produce even a system with the overall intellectual ability of an ant.

Applied AI, also known as advanced information-processing, aims to produce commercially viable "smart" systems--such as, for example, a security system that is able to recognise the faces of people who are permitted to enter a particular building. Applied AI has already enjoyed considerable success. Various applied systems are described in this article.

In cognitive simulation, computers are used to test theories about how the human mind works--for example, theories about how we recognise faces and other objects, or about how we solve abstract problems (such as the "missionaries and cannibals" problem described later). The theory that is to be tested is expressed in the form of a computer program and the program's performance at the task--e.g. face recognition--is compared to that of a human being. Computer simulations of networks of neurons have contributed both to psychology and to neurophysiology (some of this work is described in the section Connectionism). The program Parry, described below, was written in order to test a particular theory concerning the nature of paranoia. Researchers in cognitive psychology typically view CS as a powerful tool.