A Possible Evolutionary Neural Net Model of Turing's Child Brain

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A Possible Evolutionary Neural Net Model of Turing's Simple Child Brain

In 1950 Turing wrote a paper Compuing Machinery and Intelligence and suggested that one approach to building an intelligent system, that could play the imitation game, might be to start by simulating a child's brain.

“Presumably the child-brain is something like a note-book as one buys it from the stationers. Rather little mechanism, and lots of blank sheets. …  Our hope is that there is so little mechanism in the child-brain that something like it can be easily programmed.”

 While an enormous amount of research had been done relating to the brain and artificial intelligence since you will find nothing in the published literatureto suggest that Turing's hope was justified.

This paper looks at the archives of an early and very unconventional computer language, CODIL, which (like dozens of other experimental languages at the time) never became commercially viable. CODIL was designed to help a human user and a computer clerk work together symbiotically on complex problems where uncertainties made the conventional pre-define algorithm approach impractical. 

But the underlying mechanism supporting CODIL is very simple (like Turing's child brain), and could be a model of how information has passed from parents to their children for thousands of generation - making a very deep learning network. 

The assessment shows that CODIL could be considered to be a language for exchanging information between two neural networks - one the brain of the human user and the other in the computer.  This was achieved by handling information in a way that resembles human short term memory. In addition, because the human is providing the information in "network form" the computer does not need to use time-consuming trial and error learning, avoiding the learning problems of much A.I> research.

Because the work was abandoned in 1988 many of the crucial questions, such as "Could a CODIL-like model supporrt natural language?" were not examind before the project closed. As a result this paper looks ways in which the CODIL research relates to evolution of human intelligence.

Read the paper here

I would be very grateful for any comments you can make, with citations to any similar reseach I may have missed,  In particular I would be interested to know if you think the research should be restarted.

The Black Hole In Brain Research

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The following post was first published in 2011 and is relevant to my latest note A Possible Evolutionary Neural Net Model of Turing's Simple Child Brain which attempts to bridge the black hole.

The whole issue of how the brain works, and the origins of human intelligence, are matters of considerable interest, and most universities will have several very different departments which have staff researching some aspect of the area. In hospitals and medical research departments people study the effects of injuries and illnesses that effect the brain. Modern equipment can identify electrical signals and locate their sources. Computer Science Schools may have departments of Artificial Intelligence, while there is interest among psychologists, educationalists, linguists, biologists, evolutionists and many others. In each speciality there will be a mountain of publications, many of excellent scientific quality. It is quite clearly impossible for anyone to be fluent with the current research right across the board and there is so much narrow specialisation that researchers in one area may find it very difficult to understand some of the other specialities,.

So lets all stand back as far as we can and take an overall, and hopefully non-partisan, look.

While the amount of knowledge we have of the brain has increased enormously in recent years there is a problem. If we were working towards some kind of unified theory of the brain the aim would be to link all these different disciplines together in a central model. What we find in the middle is more like a large black hole with people from different disciplines kibbling round the edge. For example there is no clear route which links the neurons to language learning or the ability to play chess well. Particularly when making comparisons with animals, one is even uncertain what how the term “intelligence “ should be defined.

An analogy might help to identify the problem. An alien life form with a very different technology visits this planet and takes away a number of working personal computers, each actively running a different application. The aim to investigate the nature of the intelligence inside the boxes. They make enormous progress. They “kill” one or two and find the circuit board and the various components and study these in great detail. They design monitors which tell them which components are electrically active and examine each application in great detail. For instance they discover that the chess is a game – and they use their own technology to play the game and win.

Despite all this research they still do not understand the key to these boxes apparent intelligence. What they are missing is an understanding of the instruction set of the central processor and the way it interacts with the memory, and the way this allows information for each application to be mapped onto the memory.

I am suggesting that the “black hole” in brain research is equivalent to the one described in the analogy. We know that the brain's central processors must be neurons, working singly or in groups, and that memory must be held somewhere in the network of nerves. The brain somehow uses this arrangement to support a wide variety of tasks (often different in different people) as varied as supporting one or more spoken languages, playing chess, flying an aeroplane, earning a living or arguing with 100% conviction for (or against) the existence of a god.

The target of these Brain Storms is to explore the options for such a “brain central processor” and one option that will be examined will be to look at of an unconventional computer language called CODIL, which was designed to be human friendly and which can demonstrably support a wide range of applications. This suggests some features suggesting one possible model, but there may be others and you suggests are very welcome.

The next few Brain Storms posts will look at the evolution of Mankind and what it tells us about the evolution of man's self- named “intelligence” and the possible relation between human and animal “intelligence”. I will then describes a provisional target model for the Storm – and start looking at how far the CODIL model succeeds, and fails in other ways, to meet the target. Hopefully by this stage other people with have joined in with other ideas – so that together we can define a possible predictive model for more detailed examination.

I am exploring ideas about how the brain works and the following Brain Storms (posted between 2011-2013) record the first steps in trying to understand the theory behind CODIL. 

1. Introduction
2. The Black Hole in Brain Research
3. Evolutionary Factors starting on the African Plains
4. Requirements of a target Model
5. Some Factors in choosing a Model
6. CODIL and Natural Language
7. Getting rid of those pesky numbers
8. Was Douglas Adams right about the Dolphins
9. The Evolution of Intelligence - From Neural Nets to Language
10. The Limitations of the Stored Program Computer
11. An Evolutionary Model of the Brain's Internal Language
12. Step outside the box to understand the Evolution of Intelligence
13. How the Human Brain works - concept cells, memodes and CODIL