Toward formal models of biologically inspired, highly parallel machine cognition

The relentless march of multiple-core chip technology is creating intractable massively parallel programming challenges. High level mental processes in many animals, and their social analogs, present similar problems, and recent mathematical models addressing them appear adaptable to the multi-core conundrum. But biological and cultural evolution have taken, respectively, the better part of a half-billion years to stabilise high order mental functions in living organisms, and 10,000 years to constrain the behaviour of human institutions, in both cases with limited success. Stabilising large networks of highly intelligent devices seems as fundamentally difficult as programming them.

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