Jerry Fodor

American philosopher and cognitive scientist at MIT and later Rutgers University, the most influential defender of the computational theory of mindcomputational theory of mind, n.: The idea that thinking is a kind of computation: the mind processes information by following rules, much as a computer runs a program, and the brain is the machine doing it. in its classical, symbolic form. In 'The Language of Thought' (1975) he argued that thinking is computation over mental representations with a language-like syntax and compositional meaning (the language of thought hypothesislanguage of thought hypothesis, n.: The theory that we think in an inner, wordless mental language with its own symbols and grammar, which the brain manipulates when we reason, much as a computer manipulates code.), and his 1974 essay on the special sciences made multiple realizabilitymultiple realizability, n.: The idea that the same mental state, such as pain, could be produced by very different physical systems — human brains, octopus brains or perhaps computers — just as one program can run on different machines. a pillar of functionalismfunctionalism, n.: The view that minds are defined by how they work, not what they are made of: pain, for example, is whatever inner state plays pain's part, linking injury, other thoughts and behavior.. 'The Modularity of Mind' (1983) distinguished fast, encapsulated input modules from central reasoning, which he argued is holistic and therefore beset by the frame problemframe problem, n.: The difficulty of getting an AI to work out what does and does not change when something happens, without spelling out every one of the countless things that stay the same.. With Zenon Pylyshyn he argued in 1988 that connectionistconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols. networks cannot explain the systematicitysystematicity, n.: The way thinking and language come in connected packages: if you can understand 'the dog chases the cat', you can also understand 'the cat chases the dog'. Whether neural networks manage this has long been debated. of thought — anyone who can think that John loves Mary can think that Mary loves John — unless they implement a symbolic architecture; the argument remains central to debates over whether neural networksneural network, n.: A kind of computer program that learns a task from examples by tuning thousands to billions of connections between simple number-crunching units, an arrangement loosely inspired by nerve cells in the brain., including large language modelslarge language model, n.: A computer program trained on enormous amounts of text to predict the words that come next. At vast scale, that simple skill lets it chat, answer questions, translate, summarize and write code., generalize compositionally.