European scientists are building silicon chips containing large scale artificial neural networks (200,000 neurons and 50 million synapses, scalable to a billion neurons and 10 to the 13 synapses). (Thanks to Neal Anderson for the link.)
IBM scientists and working on “cognitive computing”, an attempt to build a new generation of computers inspired by how the brain works.
I just read the IBM press release linked to above, which is too vague to understand what’s going on. From my limited understanding, I would conjecture the following:
None of this revolutionizes the theory of computability properly so called, that is, the study of computable functions over denumerable domains (e.g., natural numbers). However, it might help develop the branch of computability theory that deals with what can be computed by certain kinds of neural networks, and with what resources. This, in turn, might help develop faster and more efficient computing components for ordinary computers.
This work may even lie outside the boundaries of computability theory, because the networks in question may operate on vehicles that do not quite constitute well-defined denumerable domains. If so, these studies might contribute to understanding the brain and perhaps to building interesting special purpose applications and to develop the relevant mathematical theories (which I would prefer not to call “theory of computation” so as not to confuse with the mathematical theory of computation in the sense above), but it would be unlikely to replace ordinary computing technology (“universal” computers like the ones we use).
Does anyone else know more about these efforts and their implications?