Parallel Models of Associative Memory

Parallel Models of Associative Memory

Parallel Models of Associative Memory

Parallel Models of Associative Memory


Presents studies of parallel, distributed, & associative memory. Offers a range of models & applications, from computer science, to neuroscience, to psychology.


A lot has happened since this collection of chapters was first printed in 1981. The basic ideas presented here are still correct, but they have been extended considerably and are now being applied to practical problems. We mention a few of the major developments here.

Of particular note is the growing distinction between those who study parallel distributed models as models of human thought processes and those who are interested in neurally inspired models for their practical applications. In 1981, only the first class existed in any numbers. Now, the majority of the attendees at some of the large scientific meetings in this area are from private industry, and their interests are primarily focussed on practical applications.

The claim has been made for decades that if we understood how the brain worked, we could make machines to mimic it. These machines might be very useful because they would be parallel, fault tolerant, and very good at computations that people perform effortlessly like perception or content- addressable memory. There is now a general feeling that this prediction is showing signs of coming true, although we are still a very long way from truly intelligent machines, and we still have a lot to learn about how computations are organized in the brain.


In terms of the sociology of the neural network field, the most important . . .

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