Massively Parallel Architectures for Al: NETL, Thistle, and Boltzmann Machines

Scott E. Fahlman, Geoffrey E. Hinton, Terrence J. Sejnowski

It is becoming increasingly apparent that some aspects of intelligent behavior require enormous computational power and that some sort of massively parallel computing architecture is the most plausible way to deliver such power. Parallelism, rather than raw speed of the computing elements. seems to be the way that the brain gets such jobs done. But even if the need for massive parallelism is admitted, there is still the question of what kind of parallel architecture best fits the needs of various AI tasks. In this paper we will attempt to isolate a number of basic computational tasks that an intelligent system must perform. We will describe several families of massively parallel computing architectures, and we will see which of these computational tasks can be handled by each of these families. In particular, we will describe a new architecture, which we call the Boltzmann machine, whose abilities appear to include a number of tasks that are inefficient or impossible on the other architectures.

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