Neural Nets or Networks of Neurons?

A comment on  The Evolution of Intelligence – from Neural Nets to Language. says:

I believe it is time we consider Post Neural Networks models, to overcome limitations of the NN model in such applications as natural language

I suspect that this was meant to be a criticism - but I agree (in the same general terms as the original comment) with the sentiment.

Part of the problem relates to terminology, the fact that I have been out of academic circles for over 20 years, and at 73 and with no east library access I am not in a position to absorb all the research in all area relating to the brain, its evolution, language, etc. carried out since I retired. As a result I will occasionally use words in a common sense "everyday" use when they also have specialist meaning to experts in one field or another.

As far as terminology goes I have used the word neural net to mean the network of neurons in the brain - and not specifically some artificial intelligence research mathematical model. There can be little doubt that the brain contains a network of neurons connecting the nerve cells - and they apparently play an important function in how the brain works - and I am sure we couldn't speak if all the neurons were suddenly removed. Thus any model of language MUST, in some way or another, depend on understanding how the neurons and nerve cells in the brain work.

One must also consider the problem of models in general and what they can and cannot do. As someone who graduated as a chemist, and did a Ph.D. relating to theoretical chemistry I am well aware that for some tasks you need multiple models. When I cook a meal I do not, for example, try to explain what is happening in terms of wave functions.

If we want to relate what the neurons are doing with natural language we need suitable models. If you ask whether a typical Artificial Intelligence Neural Net model could directly support natural language you are asking a question (in modelling terms) of whether one could use quantum mechanics to predict which sperm will fertilize an egg or whether a stored program computer's central processor could run a major air traffic control system without intervening software.

What I am saying is that if you are to relate what happens at the neuron level with the works of Shakespeare you will need intermediate models. Modern stored program computers work because they invoke a onion shell of models (called programs) between the electronic and the what the user actually sees and does at the keyboard.

So the question we need to ask is not "Can we go directly from a neural net to natural language?" - but rather "What intermediate models do we need to introduce to bridge the gap?"  CODIL was designed as a "white box" information processing tool to help people with a range of potentially open-ended tasks - and while it was not taken up commercially it has been demonstrated to be potentially very powerful. Because funding was not obtained to allow the research to continue it could well be able to support a natural language system. What I realised when I decided to pop my head up from retirement was that its architecture was compatible with at least some ideas about neural nets.

While I would be the first to agree that it may well not be THE ANSWER it at least looks as if it could provide the basis of a "first attempt" modelling of the brain's equivalent to a stored program computer's symbolic assembly language.

If this is what Post-Neural Research is looking for we are in 100% agreement.