Language is a complete system, it’s how it should be studied

Language is a complete system, it’s how it should be studied

There is a hypothesis about the symbolic system formulated by Newell and Simon and holding that the physical symbolic system has all the necessary and sufficient means to perform basic intellectual operations. Among other things, the hypothesis explains "how and why a language appears", or at least guides the corresponding research.

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Neurobiologists also appeal to the notion of symbolic conceptual systems of elements processed by the biological neural network. They suggest that a biological neural network must operate on entirely different principles than an artificial one. For example, when a symbolic element of a neural network is activated through one functional system, it leads to the activation of a deep associative relation with other functional systems where that element has been involved.

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Nowadays neurobiologists and the scientific world in general have a huge set of data and facts about the nervous system, brain, biology, etc. This set of facts and knowledge makes them doubt that AI could be a successor, let alone an analogue or even a substitute for the brain, thinking, consciousness and psyche. Yet scientists cannot suggest any alternatives — only a vast collection of facts, as we have already pointed out.

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The symbols embedded in a language are sufficient to perform intellectual operations. Language is a complete system and that is how it should be studied. It does not matter whether a language is phonetic or graphic, it has evolved and developed so that it can be used to describe the whole world including the things you can see, learn and think. This is "performance of basic intellectual operations".

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Presumably, such a "symbolic" element is engaged in many different functional systems. Such systems are part of the overall human neural network, which does not operate all the time in its entirety. Each relation or contact of an organism with the surrounding world is served by a certain number of synchronously active and working together nerve cells which represent a functional system. And the general neural network of a human being consists of these functional systems which bear all the knowledge of an organism about relations with the surrounding world.

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One of the solutions could be a merger of neurobiology and AI, but we believe that this will not bring about a positive effect. Apart from the terms "neuro" and "neuron" they do not really intersect in any way, and we can't expect such an intersection. However, TAPe, in our opinion, provides answers to many of the questions we ask that others do not seem to have answers for.

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The concept of symbols is, in fact, constantly used by scientists involved in linguistics, and even in cognitive science, as a point of reference. Terrence Deacon, an American neuroanthropologist and philosopher, believes that we cannot see the world other than in clear terms of symbols. This is basically an extension or development of the Newell — Simon hypothesis. It is through symbols that we describe what we see, what we feel, what we understand. And these symbols: a) are enough and b) are the only thing we use to define everything. So we do not describe the world as it is, but only the parts of it that can be described by symbols. And this is necessary and sufficient.

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It comes as no surprise that neurobiologists consider symbolic elements to be participating in the functioning of the biological neural network. And they are indeed symbolic; they can't be digital, can they? It would be more interesting to understand what exactly these elements are, how and where they were originally formed, by which laws they interact, rearrange and are used in thinking. And by what laws they evoke this or that element in someone's associative memory, and into which functional systems they wander off.