George Lakoff, an American linguist and professor of cognitive linguistics, once said that mathematics emerges from language. We would like to clarify that mathematics emerges from computation or the way we compute. If we replace the word "language" with "symbolic system," we can say that the logic of computation emerges from the symbolic system. As far as we know, this logic and mathematics have not been described anywhere.

The so-called AI uses mathematics in language, but linguists seem to have failed to find it. In fact, almost all large-scale translations  are now based on AI models. Although it may seem like a simple process of searching through large databases, finding the next word, and propagating errors in reverse, it does not involve understanding the essence or connections within the language.

This is not mathematics in the classical sense, nor is it linguistics. Human perception through the senses, combined with the brain, naturally forms primary elements and connections between them.

Scientists from various fields, such as neuroscientists, linguists, and psychologists, have discussed the innate mechanism of perception that allows the human brain to process information. In the mid-1970s, the concept of the Language of Thought was proposed as a hypothetical innate mechanism that enables humans to perceive reality, transform it into data, and then into information (in the conventional sense of the term). This concept was introduced by the American philosopher and linguist Jerry Fodor in the 1970s. Fodor also laid the foundation for cognitive science.

It is important to note that we distinguish between the concepts of "perception" and "information." The chain can be described as follows: reality → perception → information → processing. To turn information into data, various technologies transform, convert, recode, or reformat it into a format that is suitable for these technologies, and only then can this data be used to solve the tasks at hand. During the information conversion process, significant connections that were present in the original reality are lost. The conversion of information dramatically reduces the usefulness of the collected data. 

However, it is possible to obtain information with a much greater number of significant connections, while using much fewer resources. In fact, instead of the binary system that all devices today operate on, we need a different system with different elements that interact according to different laws. This is what we decided to focus on when we began our active research in the field of TAPe several years ago.

So, the brain does not use mathematics with roots, integrals, functions, etc. for "calculations," and it is not a computer that operates with 0 and 1. However, if we draw an analogy, the brain operates with elements that form a system, a kind of "alphabet" that we have decided to call linguomathematics. We use this neologism because we believe that it accurately describes the essence of the information perception processes that occur in the brain. These elements, which can be loosely referred to as "letters," interact with each other according to specific mathematical laws, resulting in the creation of new elements ("words" and "sentences"). In TAPe, we refer to these elements as T-bits. The Theory of Active Perception describes the laws that govern the interaction between these elements. 

So what is the TAPe?

When a person's visual analyzer perceives information ("sees"), a conditional element "takes on" a certain weight of information, and this information is used in the brain's neural network. Unlike recognition technologies that require a map with a large number of key image features, the brain only needs a minimal number of such elements to recognize an image.

Additionally, it is likely that the brain does not need to perform "calculations" every time, as we often rely on simple recognition. Furthermore, the brain can complete the image of an object that we have seen multiple times without requiring deep recognition. We use this approach in our products and technologies in the field of computer vision and video processing. In practice, this means that we need much fewer parameters to train recognition models, and much fewer computational resources and time. 

We are specifically talking about visual information, as TAPe's mathematical methods are currently developed for visual information. However, we believe that TAPe can be applied to any type of information, and the isomorphism with language further confirms this. 

For example, Noam Chomsky talks about the innate mechanism of language perception. Why is it that every person is born with the ability to learn any language? How does the human brain “calculate” such a complex system as language grammar? What are the laws that govern the combination of elements in a language?

Chomsky, along with dozens of other scientists around the world, has been trying to answer these questions. In particular, in the middle of the last century, he proposed several hypotheses and theories that have shaped the development of linguistics for decades to come. However, Chomsky did not go beyond general concepts regarding the interaction and generation of new elements (meanings) in language. 

This hypothesis has been challenged, as there is a widespread belief that language emerged primarily as a means of communication. However, we tend to agree with Chomsky's perspective. This hypothesis aligns well with the broader concept of Language of Thought, which was proposed by Fodor.

In our view, the Language of Thought is an innate mechanism through which the brain perceives information. When Chomsky speaks about the innate ability of humans to acquire any natural language through a universal grammar that is somehow “built-in” to our brains from birth, it becomes evident that we need to consider a broader concept. We propose using the concept of Language of Thought.

It is very likely that the natural language of humans was born and evolved step by step from the significant features that were initially “selected” by the brain, after which the laws of linguistics, society, and statistics were applied to each specific language, and the language was created as a means of communication. 

Within the framework of TAPe, it is the “sign” system that matters. For example, why are the elements of a language structured in a particular way? How did the initial elements that make up the language come to be? Why are they combined in a specific way, even though there may be many possible combinations? 

Our theory suggests that the Language of Thought led to the creation of the elements of a natural language in their current form, and that a natural language is a manifestation of the Language of Thought. This makes it an excellent subject for studying these manifestations through the mechanisms of TAPe.

The term "linguomathematics" can be replaced with the more common term "computation." However, our term is more appropriate because it refers to symbols rather than letters and/or numbers, which are typically associated with the concept of "computation."