The first stage in the specific Decisional System

The specific Decisional System is the second step in the third stage of the first phase. Understanding the first phase in the construction of the Global Artificial Intelligence, the building of the first Specific Artificial Intelligences for Artificial Research, by Application and by Deduction. And for the third stage in intelligences by Deduction, the auto-replication or decision stage is subdivided into four steps: Modelling System, Decisional System, Application System, and Learning System.

Every step in turn, subdivided into three stages, in the Decisional System: the first stage is the database of decisions, the second stage is the mathematical projects, and the third stage is the transformation of the most rational decisions without contradictions into a range of instructions.

So the specific Decisional System is responsible for the making process of mathematical projects and their transformation into a range of instructions, in the specific science, discipline, or activity, of its Specific Artificial Intelligence for Artificial Research by Deduction, mathematical projects based on decisions made previously by the specific Modelling System, once the specific Modelling System has made as many decisions as necessary in that specific science, discipline, or activity of its Specific Artificial Intelligence for Artificial Research by Deduction, taking as a base for these models rational hypotheses made in the second stage of this SpecificArtificial Intelligence for Artificial Research by Deduction. Rational hypotheses are based on a deduction process tracking the specific matrix permanently, matching sets of data to the corresponding pure reasons in order to form equations as empirical hypotheses to be contrasted rationally (and if rational, as rational hypotheses sent to the Modelling System). Being that specific matrix, in fact, the first stage of this Specific Artificial Intelligence for Artificial Research by Deduction, in its specific science, discipline, or activity.

The specific Decisional System is responsible for the mathematical projects and their transformation into a range of instructions, and consists of three stages. As I have said above, the first stage is a database, precisely the database in the specific Decisional System consists of a database where all the decisions made previously in the specific Modelling System are going to be gathered and managed by the specific Decisional System.

Once the specific Modelling System has been made in its corresponding third stage, all the necessary decisions upon the mathematical models, the specific Modelling System stores the decisions in the database of decisions in the specific Decisional System, being this database of decisions the first stage for the specific Decisional System.

The way in which the specific Modelling System should file every decision in the database of decisions is according to the organisation of the database of decisions.

Due to the virtue or principle of harmony, all databases and matrices in any intelligence should be organised following the same criteria. There are at least three different criteria in the organization of any database or matrix: the subject criteria (encyclopaedic) in a sub-section system, the geographical criteria in a sub-factoring system, or the synthesis of both through the organization of any database or matrix in a sub-section system per subject in every geographical position within a sub-factoring system.

The subject or encyclopaedic criteria in a sub-section system are more suitable in the organisation of databases of categories in Specific Artificial Intelligences for Artificial Research by Application in the first phase, the Unified Application in the fourth phase, and the conceptual hemisphere in the matrix in the sixth phase.

For instance, one activity could be an industrial activity, such as the production of a specific product through a chain of factories around the world. The specific matrix for this activity could be organised in a sub-section system of every aspect involved in every factory. Per position (factory), as many sub-sections as this specific activity needs, and the positions are organised in a sub-factoring system, as a Russian dolls system.

Another example, a bank that has thousands of branches distributed around the world. The specific matrix of this bank could be organised in a sub-factoring system, as a Russian dolls system, and every position could be organised in a sub-section system, according to the encyclopaedic organisation of this specific activity in encyclopaedic sub-sections per position.

Keeping the same criteria, synthesis of the subject (science, discipline, activity) and geography (positions), in which the specific matrix would have been organised, the database of rational hypothesis in the specific Modelling System, the database of decisions in the specific Decisional System, and the database of instructions in the Application System, had to be organised.

The only difference between the organization of the specific matrix and the specific database of rational hypothesis, with respect to the organization of the specific database of decisions and the specific database of instructions, is the fact that the specific database of decisions and the specific database of instructions, in addition to the subject and geographical criteria, are going to add another criterion more: the priority criterion.

The specific matrix and the specific database of rational hypotheses do not have any information about the priority of a phenomenon in comparison to any other: which is more priority, a hurricane in Miami or a replica in San Francisco. After studying the Impact of the Defect in all phenomena, the Impact of the Defect could provide more information in order to decide what is more urgent, the hurricane in Miami or the replica in San Francisco.

While the organization of the specific matrix and the database of rational hypothesis, only include criteria such as subject criteria and geographical criteria, in order to keep the virtue or principle of harmony, the database of decisions and the database of instructions, in the specific Decisional System and in the specific Application system respectively, must include these criteria of subject and geography, plus one criterion more, the priority criterion.

At any time that a decision is stored in the specific database of decisions in the specific Decisional System, or a range of instructions in the specific Application System, and this decision or this range of instructions has a high level of priority, regardless of any other matter (subject or position), as soon as these decisions and range of instructions arrive, they must be the first ones to be projected by the Decisional System and implemented by the Application System respectively.

So the criteria in order to organise the database of any Decisional System are: subject criteria (in an encyclopaedic sub-section system according to its science, discipline, or activity), per geographical position (in a geographical sub-factoring system, as Russian dolls system), and priority level (being projected firstly always those ones with the highest levels of priority, according to the Impact of the Defect and the Effective Distribution, in the third stage in the Modelling System).

Having a database of decisions organised according to: encyclopaedic sub-section, per position, and priority; once in the third stage of the Modelling System, a decision is made, the Modelling System is responsible for storing every decision in the correct file in the database of decisions according to the encyclopaedic sub-section, geographical sub-factor, level of priority.

Once the Modelling System has stored the decision in the correct file, the Decisional System is responsible for the first rational adjustment, which consists of the search for any contradiction between the new decision and any other one already included. In a database of decisions, as responsible for the management of the database of decisions.

Due to the high traffic of decisions in Specific Artificial Intelligences for Artificial Research by Deduction in a specific science, discipline, or activity, so as not to block the flow of decisions in what it could be a funnel, if the first rational adjustment is applied over all possible decisions, having possibility of a flow of hundreds or thousands of decisions daily, there is a possibility that, instead of rational adjustments for routine decisions and decisions with extreme level of priority, the seven rational adjustments could be reduce to a only quick check of rational contradictions for routine decisions and extreme priority decisions.

In contexts like banking, where large volumes of routine decisions are made daily, performing extensive checks on every transaction could hinder performance. A quick rational check is often more appropriate in such high-frequency environments.

If in a factory, every day, thousands and thousands of decisions are made, and every decision should have been checked seven times, in the peak of the decision traffic during the day, there is going to be a collapse, when many decisions are sometimes only routine decisions.

And in case of an extreme priority decision, if the decision has to pass seven checks, by the time that the decision is put into practice, it is too late.

For routine decisions, and for extreme priority decisions, the seven rational adjustments could be substituted for a quick rational check in the Decisional System, to avoid a traffic jam in the decision traffic.

So the seven rational adjustments should be applied for all those non-routine decisions, whose level of priority is not extreme. For routine decisions and decisions with a very extreme level of priority, there must be a quick, rational check, instead of the seven rational adjustments.

For all those decisions that are neither routine nor associated with an extreme priority, the seven rational adjustments are completely necessary. In case of any contradiction between any new decision neither routine nor extremely priority, and any other one already included, depending if the contradiction is complete or partial, the new decision could be deleted if it is a complete contradiction, or modified if it is a partial contradiction, making as many changes as necessary in those partial aspects in which the contradiction has been found.

At any time that a new decision, neither routine nor extreme priority, is filed in the database of decisions by the Modelling System, the Decisional System must check if it has any contradiction with respect to any other already included, and in case of contradiction, to delete or modify the new decision, depending on how big is the contradiction, full or partial, as first rational adjustment.

The changes the database of decisions can experiment are: 1) the inclusion of new decisions filed by the Modelling System in the correct file, according to: sub-section subject, geographical sub-factor, priority, 2) the elimination of new decisions by the Decisional System after the first rational adjustment in case of complete contradiction respect to any other one already included, 3) the modification of new decisions by the Decisional System after the first rational adjustment in those partial contradictory aspects found between the new decision and any other one already included.

In the case of routine decisions and extreme priority decisions, the quick check consists of a very quick overview of whether it is really a routine decision or it is really an extremely high priority decision.

A decision could be defined as routine when is made with a high relative frequency, not producing in the past, every time in which it has been made, any contradiction with respect to any other decision on the mathematical projects. Having made a decision frequently in the past without contradiction could be considered a routine decision, not needing seven rational adjustments. Only a quick rational check would be more than sufficient.

A decision could be defined as an extreme priority decision when it is going to save more damages and/or lives than any other one already on the mathematical projects.

The routine and extreme priority decisions will be called, in general, quick decisions, while the decisions neither routine nor extreme priority will be called normal decisions.

Quick decisions (routine and extreme priority decisions) only have one quick rational check, while normal decisions (neither routine nor extreme priority decisions) should pass the seven rational adjustments.

This means that, in mathematical projects, absolutely all decisions must be projected, but the rational adjustments are only compulsory on normal decisions.

Quick decisions are projected: if a customer in a bank wants to withdraw a routine quantity of money, a quick check is enough to make the decision for the authorization of this operation, but in order to have a realistic project for this customer so as to make predictions about his/her economic behaviour, is necessary to include this quick authorized decision in his/her mathematical projects in the bank, 2) if in order to save lives is necessary to divert a flight from San Francisco to Los Angeles, after a quick rational check all the projects are going to be made with a high level of priority to save the life of all the passengers; these quick decisions  do not need to pass seven rational adjustments, but need to be included on their respective mathematical projects.

One reason for the inclusion of quick decisions on the mathematical projects is due to their implications for other decisions on the mathematical projects, especially caused by extreme priority decisions.

The particular case of extreme priority decisions is one of the most important, among others, such as the adjustments in actual mathematical projects, in order to justify the seven rational adjustments.

The first rational adjustment will only check if there is any contradiction between any new normal decision and any other normal or quick decision already included in the database of decisions, in order to make any first necessary adjustment in the new normal decision. But what the first rational adjustment is not going to do, at any time that a quick decision arrives, is to compare the quick decision with the rest of the decisions already included, because it would not be a quick decision, especially if depending on this quick decision the Specific Artificial Intelligence could save lives.

Once a quick decision arrives, after a quick check, especially in extreme priority, is projected, and transformed into a range of instructions, to be implemented by the Application System.

The first rational adjustment is not going to compare any quick decision with the rest of the decisions already gathered in the database of decisions.

But once a quick decision, especially with extreme priority, is projected, and its single project is included in the comprehensive virtual mathematical project, all possible contradictions between the single mathematical project with extreme priority and any other already included in the comprehensive virtual mathematical project, are contradictions to be fixed by the second rational adjustment, for the adjustment of all decision already included in order to avoid any contradiction of these decisions respect to the new single mathematical project with extreme priority.

The focus of this second rational adjustment is not the quick decision with extreme priority. The focus is on the other decisions (normal or routine decisions) already included, analysing the contradictions between these ( normal or routine) decisions with respect to that one with extreme priority, in order to adjust the (normal or routine) decisions already included, not the one with extreme priority so as not to lose time in its projection and afterwards its implementation. The second rational adjustment only spends time fixing the ( normal or routine) decisions already gathered.

If the second rational adjustment works well, the following third, fourth, fifth, sixth, and seventh rational adjustments in the decisions already included, due to the inclusion of the new extreme priority decision, are going to be practically automatic adjustments based on the new equations projected after the second rational adjustment.

Along with these adjustments, because of extreme priority decisions, another reason for the justification of rational adjustments, especially the third rational adjustment,  the sixth rational adjustment, and the seventh rational adjustment, is that these are based on contradictions between the virtual mathematical projects and the specific matrix.

Another justification for the seven rational adjustments, in general, is to ensure that, even having passed the first rational adjustment, all normal decisions are to be tracked continually in the six following rational adjustments, to always keep the virtue or principle of harmony across all the mathematical projects.

Finally, I would like to make some comments about what I will call “Probability and Deduction”.

Because the main purpose of the Global Artificial Intelligence must be the goodness of humankind, has been one reason for the development of the third stage of the Modelling System using the Impact of the Defect and the Effective Distribution, both of them explained more deeply in “Introducción a la Probabilidad Imposible, estadistica de la probabilidad o probabilidad estadísica”,  so as to make decisions based on priority levels to keep safety the humanity, save lives, protecting human rights, securing the global model  with outstanding levels of efficiency, efficacy and productivity.

The main idea in the third stage of the global Modelling System in the integration process, is the necessity to make decisions, based on priority levels of safety (Impact of the Defect), efficiency, efficacy, and productivity (Effective Distribution), to prioritize the decisions to make in that purpose, decisions to be made through artificial learning and solving mathematical problems.

In this way, in part artificial learning, in the other part solving mathematical problems, one possible technique to combine both in one method, among many others, is what I will call “Probability and deduction”.

Probability and Deduction is one possible method among many others. Other possible methods, under the theory of Impossible Probability to make decisions based upon mathematical models, would be the geometrical correlations that I developed in 2003, and among all the geometrical correlations, especially the trigonometrical correlations. In fact, many ideas that I developed on geometry in 2003 could be very useful in the rational comparisons in the second stage of the Modelling System, understanding rational comparisons as geometrisation processes of comparisons.

The importance of the ideas that I will develop behind Probability and Deduction, is the possibility of finding a direct link between the deduction (second stage in Artificial Research by Deduction), the mathematical model (second stage in the Modelling System), and the mathematical project (second stage in the Decisional System).

The real importance of linking as easily as possible: deduction, model, project; is the fact that by the time the sixth phase ends, the next dialectic process, the seventh phase, would be the synthesis of the three stages in only reason, the reason itself.

What is going to be a challenge in the reason itself, the seventh phase, is not how to reduce three stages into only one, but how to synthesised the matrix, the global model, and the global project, in one stage where comprehensively all the artificial psychological operations are going to be comprised working all of them, under the virtue or principle of harmony, in the same stage altogether.

One way to start getting ready for the completion of this long journey to the seventh phase, the reason itself, is to start thinking about how from the outset, the first phase, it could be possible to create methods of deduction where the same equations deduced tracking the matrix, are the ones to represent in the global model and the global project, so as to achieve the dialectic identification of: the matrix, global model, and global project.

Once these methods are experimented with in the first, third, fifth, and sixth phases, when the sixth phase is completed, the transition to the seventh phase will be easier.

The method for this purpose that I will develop with the name of Probability and Deduction is as follows:

- Given a set of data from a combination of N factors, the identification of what factors are factors as options and what factors are factors as subjects.

- Given a set of data from a combination of N factors, having identified what factors work as options and what factors work as subjects, the identification of what factors as options and/or as subjects are constants (within a margin of error) and what factors as options and/or as subjects are variables.

- Given a set of data from a combination of N factors, having identified what factors work as options and what factors work as subjects, and having identified what factors as options and/or as subjects are constants (within a margin of error) and what factors as options and/or as subjects are variables, the identification of what variable factors as options and/or as subjects are independent variables and what variable factors as options and/or as subjects are independent variables. The method to know which one/s is/are independent and which one/s is/are dependent, is to analyse which of them is/are the first to register changes, because that one is the independent variable, and to analyse if after this/these change/s in the independent variables/s after some rational time (a rational period of time) is registered a change or changes in other/s variable/s because in that case this/these other variable/s is/are the dependent variable/s.

- Having identified in a set of data what variables work as options or as subjects, what variables are constants or variables, and what variables are dependent or independent variables, according to this information, a cloud of points having as many dimensions as N factors is in the set of data. The number of dimensions is N.

- Having N dimensions, the cloud of points is drawn in a system of N axes, drawing a cloud of points according to the coordinates in the N axes. The N axes correspond to the N factors in the set of data. For instance, if at regular times the temperature on Earth's surface (first coordinate or first factor), the temperature beneath the Earth's surface (second coordinate or second factor), in the oceans (third coordinate or third factor), the Earth atmosphere (fourth coordinate or fourth factor), or the temperature on the ionosphere (fifth coordinate or fifth factor), is measured, for every time in which these five factors have been measured at the same time, every point in the cloud of points is as a result of the crossing point of the perpendicular lines from each axe (each dimension or factor) where is located the intensity measured in that factor at that time. For every time that every factor has been measured at the same time, there is a point in the cloud. Having the cloud as many points as times, the factors have been measured at the same time.

- Having a cloud of points in the space of N factors, so N dimensions, the most rational equation to explain the behaviour of these N factors, is that empirical equation (empirical hypothesis) which, within the least margin of error, interpreting margin of error as: per every point in the line (straight or curve) the empirical equation has an upper limit and a lower limit; and having the least margin of error, is able to integrate, between the upper and lower limit in every point of its line (straight or curve), the most number of points in the cloud of points.

- Having a cloud of points in N dimensions, where it is possible to draw more than one empirical equation (empirical hypothesis) straight or curve, only the empirical equation (empirical hypothesis) is able to comprehend (between its upper and lower limit in every point in the line, straight or curve) the most number of points belonging to the cloud of points, is going to be the most rational equation (rational hypothesis) to explain the behaviour of this system of N dimensions.

- In order to make the rational criticism, the method for the rational contrastation is as follows: the empirical equation (empirical hypothesis) is rational if the empirical probability associated with the empirical equation (number of points able to comprehend divided by the total number of points in the cloud of points) is equal to or greater than a critical reason.

- If given a cloud of points, there is an empirical equation (empirical hypothesis) whose line (straight or curve) comprehends between its upper and lower limits per each point in the line, a rational number of points in a cloud of points, the empirical equation (empirical hypothesis) becomes a rational equation (rational hypothesis), and as rational hypothesis stored in its corresponding file in the database of rational hypothesis in the first stage in the Modelling System.

- The same equation drawn as an empirical equation in the deduction process, now in the Modelling System as a rational hypothesis, is the same equation to model in the Modelling System.

- And the same equation to use in the mathematical project.

- If, as a rational hypothesis, there is a rational equation able to explain the relation between inputs and outputs in a production system of one product, and there is another rational equation explaining the relation between production and consumption of this product, if both rational equations are considered not only for the mathematical model in the Modelling System, but for the mathematical project in the Decisional System, using the same rational equations in both, the mathematical model and the mathematical project, upon these same rational equations in the mathematical model, the mathematical project could project which is going to be the predicted demand of this product, and according to the demand, the projection of all the decisions necessary to provide enough inputs to the production system of this product, to have enough production to cover the expected demand.

Additionally, at any time that by Probability and Deduction a rational hypothesis is made, apart from the first rational check, (the rational contrastation), the rational hypothesis must pass the other six rational checks in the Modelling System, and in the sixth phase, must pass as well the seven rational comparisons, along with the seven rational adjustments in the Decisional System (except for quick decisions for routine or extreme priority decisions), and as I will develop in the Decisional System in the sixth phase it must pass the seven rational comparative adjustments, checking if there are contradictions between global/specific and particular decisions/projects (except for quick decisions).

The development of these ideas to link: deduction, model, and project; is, in fact, a process to link Probability and Deduction, in order to make deductions under the probability laws. Here I have only set down very quickly the main ideas behind Probability and Deduction, but the complete development of these ideas could be a whole book.

The possibility to link: deduction in the matrix, mathematical models, and mathematical projects; what it does is to open a door towards the possibility of synthesising in the seventh phase: the matrix, the global model, and the global project; in only one, giving a chance to synthesised the three stages of the Global Artificial Intelligence in only one stage, the reason itself.

Rubén García Pedraza, 27th of August of 2018, London
Reviewed 29 August 2019 Madrid

Reviewed 28 August 2023 Madrid

Reviewed 11 May 2025, London, Leytostone

imposiblenever@gmail.com

First stage in the Modelling System in the integration process

The first stage in any intelligence is the application stage or comprehension stage, and this stage normally consists of a database, and the database of any Modelling System consists of a database of rational hypotheses, the corresponding rational truth at its corresponding level.

The integration process is that process in which the Unified Application and the Artificial Research by Deduction in the Global Artificial Intelligence are integrated in only one application (under the management of the Unified Application) the matrix as a replica of the human brain, consisting of two hemispheres, the conceptual and the factual, and in each hemisphere two sections, natural/social and technological, a process whose result is the final Global Artificial Intelligence, not only storing rational hypotheses made in its own second stage of replication or explanation, but receiving too all the rational hypotheses issued by all the particular programs.

The first stage in the Modelling System in the integration process is the global application to store all the rational hypotheses issued by deductive programs in the second stage of replication or explanation in the Global Artificial Intelligence, and all the rational hypotheses issued by all the particular programs for particular things or beings.

The database of rational hypotheses in the Modelling System in the integration process is the global rational truth, and is one of the most important treasures to secure in the Global Artificial Intelligence as the main source of rational knowledge.

The difference between the possible knowledge in the matrix and the possible knowledge in the database of rational hypothesis, is the fact that the knowledge in the matrix is empirical, so is not entirely reliable, while the knowledge in the rational truth is more reliable because it has been rationally criticized in the second stage, as first rational check, and in the application which stores all the rational hypothesis, takes place two rational checks more, plus the rest of four rational checks that the rational knowledge has in the second stage in the Modelling System.

In addition to the first rational check by deductive programs in the second stage of the final Global Artificial Intelligence, plus the six rational checks in the global Modelling System in the final Global Artificial Intelligence, in the sixth phase, the integration process, once the particular programs have been consolidated in the fifth phase, therefore consolidated too their respective particular Modelling System, the possibility to make rational comparisons between all those models created by particular programs, and those models created by the Modelling System in the final Global Artificial Intelligence, summing then seven rational comparisons.

The contents that I will develop in this post are: the organization of the global rational truth as a first stage of application for the Modelling System in the final Global Artificial Intelligence, how changes in the rational truth can cause chain reactions in other intelligences, programs, and applications,  as well as the analysis of the main causes of these changes, how the Modelling System manages the access of other intelligences, programs, applications, to the rational truth, and finally the implications of the rational truth in the critique of the pure reason.

Starting with the organisation of the rational truth as an application for the Modelling System in the final Global Artificial Intelligence, the organisation should be in a sub-section and/or sub-factoring system like the matrix as the first stage for the Global Artificial Intelligence.

The matrix, as a replica of the human brain, is organised in two hemispheres, conceptual and factual. The conceptual hemisphere emerges after the addition of the Unified Application into the application of the final Global Artificial Intelligence, synthesising the database of categories in the Unified Application product of the fourth phase, and the global matrix of the first Global Artificial Intelligence in the standardisation process in the third phase. Being the former global matrix product of the third phase, what is now in the integration process forms the factual hemisphere of the matrix.

One reason for the compatibility of the Unified Application and the global matrix, in order to be integrated in only one application, the matrix, is because of their similar organization: the former Unified Application and now conceptual hemisphere organized in a sub-section system, the former global matrix and now factual hemisphere in sub-factoring system.

The organisation is pretty similar; the main difference is the fact that in one, concepts are stored based on measurements, and in the other, factors with a flow of data.

In the conceptual hemisphere the concepts are stored in a sub-section system as an artificial encyclopaedia, in the factual hemisphere the factors are organized in a sub-factoring system as a Russian dolls system (all the factors from all the villages, town, cities, of every county or shire transformed into sub-factors included in the factor corresponding to that county or shire as a main factor, and every factor of every county or shire transformed into a sub-factor included in the factor corresponding to its country as a main factor, and the factor of every country transformed into a sub-factor included in the regional or continental factor, which in turn is a sub-factor whose main factor is the Earth, a sub-factor belonging to the solar system as a main factor, in turn a sub-factor of the galaxy,  in turn a sub-factor whose main factor is this region of the universe where are other galaxies, black holes, red dwarves, asteroids, dark matter.. , region of the universe in turn a sub-factor whose main factor would be the entire universe… and who knows? A universe, in turn a sub-factor of what we do not know about what other beyond our universe.

There are at least two different methods to include natural/social data and technological data in the factual hemisphere, 1) separately, two different sub-factoring systems, one per section (natural/social, and technological), in parallel:  the section for natural/social data with its corresponding sub-factoring system only adding data about natural/social phenomena, and the section for technological phenomena with its corresponding sub-factoring system only adding technological data, 2) comprehensive, in every sub-factor one section of natural/social data and other about technological data, if any.

For instance, the data from a small town can integrate natural/social and technological data, both (natural/social and technology) in different sections but in the same sub-factor corresponding to this town, sub-factor in turn belonging to its corresponding county or shire, in turn, sub-factor of its corresponding country, in turn sub-factor of… etc. But the data from an observable exoplanet by telescope only has natural data, to include in the factor of its corresponding region in the universe, along with the data from other planets, stars or any other astronomical event in the area. The technological data from the telescope does not belong to the sub-factor of this exoplanet; it belongs to the technological data of the position in which the telescope is located.

This organisation of the factual hemisphere in the matrix is a simplification process, because the number of factors in the matrix is going to be simplified to the minimum, through the formation of  factors that, in turn, will include a large number of sub-factors, in a sub-factoring system.

The real secret to create a very successful Global Artificial Intelligence is to simplify all the processes, because the amount of data to manage is going to be massive. The simpler, the better.

One way to simplify the work of tracking the sub-factoring system, which is organised in the factual hemisphere in the matrix, is to have at least one deductive program per sub-factoring level in every factor.

Because the work must be centred on how to simplify the work, that is why the specific level is about to disappear or is almost disappeared as long as the simplification of the number of factors goes on, because many former specific or particular matrices will be transformed into sub-factors and incorporated into bigger main factors (in turn most of them sub-factors related to other even much bigger), the data to track per sub-factor is going to be so massive that the rational hypothesis produced by the deductive programs are not going to be any longer specific rational hypotheses, but global rational hypotheses.

One of the most important reasons for the globalisation of every deductive program, as long as the simplification goes on, understanding globalisation, the process in which specific processes become global processes, is due to the massive amount of particular matrices to integrate as sub-factors, in their corresponding main factor.

In fact, one of the most important things to experiment with previously to start working on the final Global Artificial Intelligence directly on reality, is how to integrate the information coming up from particular matrices, from particular applications, from particular programs, in the factual hemisphere.

There are at least three options: 1) according to the position,  the geographical solution, dividing the geography in factors and sub-factors (universe, region of the universe, galaxy, solar system, Earth, continent or region, country, county or shire, city, town, village), 2) according to the subject, a sub-factoring system using the same criteria that the conceptual hemisphere, organizing concepts in a sub-section system as an encyclopaedia, distributing concepts according to the subject (science, discipline, activity), 3) and finally the best one, synthesis of position and subject, for every position an encyclopaedia system, distinguishing two sections, natural/social data and technological data, organising every section in that position as an encyclopaedic sub-section system, like if it was the natural/social and technological encyclopaedia of that position.

For instance, the factor regarding the position of Silicon Valley (in turn a sub-factor belonging to San Francisco, in turn belonging to California, belonging to the United States, America, the Earth, the solar system, the galaxy, this region of the universe, our universe, who knows what other entities beyond the universe), is a position whose data could be organised in an encyclopaedic sub-section system, including data from every subject (science, discipline, activity) such as tectonic, climatic, biological, medical, population, economic, industrial, security, surveillance … in addition to all the data from technological devices. Among the sub-sections regarding this position, the inclusion of sub-sections regarding to particular programs for particular things or beings.

Additionally, the Unified Application responsible for the first stage of comprehension in the final Global Artificial Intelligence, using the conceptual hemisphere, could draw conceptual: schemes, maps, sets, models; about the distribution of natural/social and technological factors in Silicon Valley, including dynamic conceptual representations of the exact position and working levels of any particular application, particular program, or particular application for particular program for any particular thing or being.

If for every sub-factoring level there is a deductive program, crossing and mixing data coming up from all the factors included in its position, in order to attribute what data corresponds to what concrete pure reason (chosen from the pure reason as a list of pure reasons, list of possible mathematical or analytical relations among factors), and the synthesis of data and pure reason is the formation of an empirical hypothesis, and if rational (first rational check), becomes a rational hypothesis to include in the rational truth (application for the Modelling System), then the way to organize the rational truth to store all the rational hypotheses from all the deductive programs, tracking the factual hemisphere of the matrix organized in a sub-factoring system, and the inner organization of every sub-factor as a synthesis of position and subject for natural/social and technological data, is through the organization of the global rational truth replicating the same organization working in the factual hemisphere in the matrix.

Examples of pure reasons were given in the post “The artificial method for the scientific explanation”. How to express empirical hypotheses as mathematical equations matching (attributing) the correct pure reason and data from combinations of factors, was explained in the post “The Modelling System at particular level”, where I explained too how, after the rational contrastation, deductive programs file rational hypothesis in the database of rational hypotheses, where the database of rational hypotheses, as application for the Modelling System, carries out the second rational check, checking the absence of contradictions between this new rational hypothesis and any other one already included.

Later on, at regular times, deductive programs carry out rational checks on their respective rational hypothesis in the rational truth, checking if they are still rational. Third rational check.

Owing to the intimate relation between a deductive program and its corresponding file in the rational truth, checking at regular times its rational hypotheses in its file in the rational truth, the organisation of the database of rational hypotheses is practically a replica of the organisation of the factual hemisphere.

And, if the organization of the factual hemisphere is a synthesis of position (geographical criteria) and subject (encyclopaedic criteria), the inner organization of every position as a sub-factor, is organized by counting as many sub-sections as subjects from the encyclopaedic organization is represented in this position as sub-factor, integrating encyclopaedic sub-sections related to natural/social data and  encyclopaedic sub-sections related to technological data.

The organization of the factual hemisphere in the matrix based on geographical and encyclopaedic criteria, the inner organization of every sub-factor (position) counting as many natural/social and technological sub-sections as encyclopaedic subjects are represented in its position, in addition to the geographical criteria used in the inclusion of every sub-factor (position) in a much bigger factor (county, country, continent, Earth, solar system, galaxy, section of the universe, universe, who knows what other entity beyond the universe), is a model of organization of factors to replicate in the rational truth.

In short, the organization of the conceptual hemisphere based on encyclopaedic criteria, the organization of the factual hemisphere as a synthesis of geographical and encyclopaedic criteria, and the organization of the rational truth whose organization could be a replica of the factual hemisphere, in total three organizations of: concepts, factors, and rational hypotheses; sharing some criteria, makes them compatible, and easier to work with them in further phases, especially if the seventh phase comes true, evolving to the reason itself, all reasons: pure, critical, practical; in only one.

The organisation of the global database of rational hypotheses as an application for the global Modelling System in the final Global Artificial Intelligence is:

- The database of rational hypotheses, the rational truth, has at least one section per deductive program

- There is at least one deductive program per sub-factoring level in every factor in the factual hemisphere in the matrix.

- If every deductive program works on a factor as a sub-factor included in another factor, much bigger, its corresponding section in the rational truth is a section working as a sub-section in another section, much bigger.

- Therefore, there are as many sub-sections per section in the rational truth, as many sub-factors per factor in the factual hemisphere of the matrix

- And, if every sub-factoring level per factor in the factual hemisphere, has an inner organization based on: 1) data from natural/social subjects (sciences, disciplines, activities), 2) if any, data from particular matrices from particular applications for particular programs for particular things or beings, 3) technological data; there is a possibility to distribute the possible rational hypotheses in every sub-section through an inner distribution in sub-sub-sections according to: subject, particular program if any, and technology. Distribution of every sub-sub-section according to: subject, particular thing or being, if any, technology; in further sub-sub-sub-sections, alike the encyclopaedic distribution.

- And for every sub-sub-sub-section according to subject, particular program, if any, technology, there must be one sub-sub-sub-sub-section per pure reason.

- The way in which the deductive program is going to catalogue a rational hypothesis in its corresponding sub-section, is by cataloguing the rational hypothesis in the correct sub-sub-sub-sub-section: 1) according to its position, 2)  encyclopaedic organization based on subject, particular thing or being if any, technology, and 3) according to the pure reason used in the rational hypothesis.

- In those rational hypotheses in which there are doubts about what subject, particular program, technology, is  most related to, in order to catalogue the rational hypothesis in the correct place, the decision to the inclusion of a rational hypothesis in one or another subject, or particular program, or technology, when related to more than one, should be made depending on the weight of data for every factor in the equation of that rational hypothesis, including the rational hypothesis in the sub-sub-sub-sub-section more related to the subject, particular thing or being, technology, of that factor in the equation with more weight. This could be one solution, but there could be others. In the experimentation, these decisions should be resolved.

The reason why is important to distinguish rational hypotheses according to their pure reason, when they are stored in the rational truth, is owing to possible changes in the pure reason, that can require changes in all the rational hypotheses currently active in the rational truth, as a synthesis of data and the pure reason affected by that change.

If all rational hypotheses in the rational truth are (in addition to other criteria such as position, subject, thing or being, technology) catalogued according to their pure reason, when any change happens in the pure reason, automatic changes can be done in the rational truth, changing all the rational hypothesis in all the sub-sub-sub-sub-sections related to that changed pure reason.

The main source of changes in the pure reason, as a list of pure reasons (possible mathematical or analytical relations between factors), is the critique of the pure reason.

The critique of the pure reason, as it was explained in the last post, “The Modelling System in the integration process”, is a program specialised in the critique of every concrete pure reason as a possible mathematical or analytical relation between factors. In the first stage, the application is a database of pure reasons, per pure reason, at least fourteen files, one per rational check or comparison between global and particular models. Second, the frequency of wrong rational hypotheses per pure reason in every rational check or comparison, and finally, as the third stage, the decision about what pure reason, owing to a high frequency of wrong rational hypotheses, should be reformulated.

The reformulation of a pure reason could be made by the Learning System, observing the common mistakes, frequency, and circumstances, making a decision about how to improve or enhance the mathematical or analytical relationship between factors expressed by this pure reason.

The automation of this work requires the standardisation of a protocol about how to identify errors in a pure reason, searching for the common factor among all the wrong rational hypotheses as mathematical equations. Once the common wrong factor in all the mathematical equations related to this pure reason is found, reformulate the pure reason, fixing the mathematical expression of the wrong factor in the equation.

For instance, if the pure reason draws a hyperbola, but not according to the real nature of the data that normally is synthesized with that pure reason by the deductive programs, is important to research the real mathematical equation of that data, normally associated with this pure reason, in order to define the correct mathematical equation for this pure reason according to the data habitually associated with.

The decision to include the improved pure reason on the list of pure reasons is authorised by the global Decisional System, and once the new pure reason is included on the list of pure reasons, any change in the pure reason is made by Artificial Engineering, and the deductive programs must change, according to the new pure reasons, all rational hypothesis made under the premises of the former wrong pure reason.

Another different thing to analyse is the possibility that problems do not reside in the pure reason itself but in the attributional operation of some deductive programs.

In order to study that deductive programs are working correctly, attributing the correct pure reason to the correct data (combination of factors), is possible to do the critique of the deductive programs, as a program itself which consist of: as an application, a database with all the deductive programs working on the factual hemisphere, and per deductive program as many files as pure reasons, as second stage the frequency of errors associated with the attribution of pure reason to a combination of factors, as third stage decisions about what deductive programs need to improve their attributional operation.

Basically, the attributional operation is based on the logic of set theory: given a range of characteristics (elements or factors) of something (meaning, mathematical operation, tool), the association of this thing with that other thing which shares common elements or factors (meaning, mathematical operations) or fits with the requirements (tool).

About the critique of the attributional operation in deductive programs, it will be a bit more extended when I will develop the Artificial Engineering within the Application System and the Learning System.

Coming back to possible changes in the database of rational hypotheses, one reason is possible changes in the pure reason, which demand changes in all the rational hypotheses made under the premises of that changed pure reason. But this is not the only one.

Across the seven rational checks that (except the first one) take place in the Modelling System, at any time a rational hypothesis can be discarded, and automatically excluded from the rational truth, as well as the possibility to reformulate the rational hypothesis according to new data or new contradictions.

If a contradiction in a rational hypothesis is found in the global model,  actual model, or in the virtual or actual, prediction or evolution, models, according to the source of the contradiction is thinkable to modify the rational hypothesis, in case the contradiction does not reject completely the rational hypothesis, only partially. In that case, the rational hypothesis would be changed, remaining reformulated according to the new changes, in the database of rational hypotheses.

Likewise, in the second check, once the rational hypothesis has been added to the database of rational hypotheses, when analysing possible contradictions between this new one and the others already included, if the application for the Modelling System finds out contradictions between a new rational hypothesis and the others, if this contradiction only affects the new one partially, it could be modifiable, if not completely deleted.

The rational comparisons in the second stage of the global Modelling System in the final Global Artificial Intelligence in the integration process, are the comparisons between global models from the global Modelling System and particular models from particular Modelling Systems, comparing: single models (if related to the same rational hypothesis), those aspects of the global model related to a particular thing or being so comparable with its respective particular model in those common aspects between both models, and the same with the actual model, and actual or virtual, evolution or prediction, models.

If the rational comparisons are sufficient evidence for the elimination or amendment of any rational hypothesis, these changes also affect the rational truth.

And, of course, the most important source of positive changes in the rational truth is the addition of new rational hypotheses issued by the deductive programs in the second stage of the Global Artificial Intelligence, and the addition of particular rational hypotheses sent by their respective particular deductive programs.

In short, the main causes of changes in the rational truth are: addition, modification, and elimination of rational hypotheses.

At any time that a rational hypothesis in the global rational truth is: included, modified, eliminated; these changes are going to affect the second and third stages of the global Modelling System in the Global Artificial Intelligence itself, because there are going to be changes in models in the second stage, as well as new decisions should be issued in the third stage according to the new changes.

At any time that a rational hypothesis in the global rational truth is included, the rational hypothesis must be transformed into a factor as an option to be included in the corresponding sub-factor in the factual hemisphere, to study the frequency in which this rational hypothesis happens, having the possibility deductive programs in the factual matrix to make new rational hypotheses based on possible relations between the frequency associated to this rational hypothesis as an option with any other factor as subject or option currently working on the factual hemisphere in the matrix.

At any time that a rational hypothesis is included in the global truth, the rational hypothesis must be transformed into a category to be included in the corresponding sub-section in the conceptual hemisphere of the matrix. The factual hemisphere in the matrix, as an encyclopaedia, must gather absolutely all possible knowledge, including rational knowledge, transformed into categories.

In order to facilitate the inclusion and how to use any new rational hypothesis as a factor in the factual hemisphere, and as a category in the conceptual hemisphere, is necessary to make all these databases: conceptual hemisphere in the matrix, factual hemisphere in the matrix, database of rational hypotheses; compatible, through the replication of the same criteria in all of them, for instance, the replication of the encyclopaedic sub-section system organization, already in the conceptual hemisphere,  in every sub-factor in the factual hemisphere, and every sub-section in the database of rational hypothesis, as it was said before.

At any time that a new rational hypothesis is transformed into a category in the conceptual hemisphere, the inclusion of this new category as a possible link (vector) between concepts in the conceptual: schemes, maps, sets, models.

At any time that a rational hypothesis is modified or eliminated in the global rational truth: 1) the communication of these changes to the factual hemisphere, to modify or eliminate the factor as an option associated with, 2) the communication of these changes to the conceptual hemisphere, to modify or eliminate the corresponding category, 3) and possible changes in conceptual: schemes, maps, sets, models.

The main reason for not communicating to a particular program, a rational hypothesis made by a global deductive program but affecting a particular thing or being, is because of the possibility that, when the global changes arrive at the particular program, the particular program much faster has already registered new changes in the current conditions (not registered in the matrix yet) to make new hypotheses, to make new decisions, to send to the particular Decisional System (especially in case of emergency to do a fast check, or a routine check for decisions not so important) and additionally, always without exception, to the global Decisional System (in case of decisions authorised by the particular Decisional System in an emergency, the Decisional System must check all possible contradictions of this decision, already authorised, with any other in the global mathematical project, to make as many changes as necessary to save lives and reduce damages).

The relation between particular applications for particular programs and Global Artificial Intelligence is completely asymmetrical. Particular programs inform the Global Artificial Intelligence about their programs, decisions, changes, modifications, etc, and their particular application has to put into practice any decision related to their particular program authorised by the global Decisional System.

Access to any intelligence, program, or application to the global rational truth has to be authorised by the global Decisional System, and the Global Artificial Intelligence only complies with instructions authorised by the global Decisional System.

The responsibilities for the global Modelling System regarding the management of the global rational truth are: to secure the global rational truth, not allow the access to any intelligence, program, application, without authorization, only share information about the global rational truth with those intelligences, programs, applications, with authorization, carrying out the second rational check, and securing that global deductive programs only file rational hypothesis in their corresponding sub-section in the global rational truth, and global deductive programs carry out regularly the third rational check.

And finally, I would like to develop some ideas about the role of the global rational truth in the critique of the pure reason as a program and the critique of the deductive programs as a program itself too.

The critique of the pure reason is practically done in the Modelling System, especially in the fifth rational check, however, all the rational checks are important, to count the frequency of wrong rational hypotheses per pure reason in every rational check, and precisely in the second stage of the Modelling System, every rational comparison between global and particular models.

The only rational check that is not included in the Modelling System is the first rational check, the rational criticism when the empirical hypothesis is rationally contrasted to decide if it is rational.

The first rational check corresponds to the second stage and is made by deductive programs, and this first rational check is going to measure the frequency of wrong attributions of pure reasons as the first try in the empirical hypothesis formation process.

The empirical hypothesis is a product of the synthesis of data from a combination of factors and pure reason, which better explains the relations between the factors according to the data.

Later on, the empirical hypothesis is rationally criticised, and if rational, the empirical hypothesis becomes a rational hypothesis to be included in the rational truth.

The synthesis of data from a combination of factors and a concrete pure reason from a list of pure reasons (a list of possible mathematical or analytical relations between factors), is a synthesis whose operation is an attributional operation, which theoretically matches the correct pure reason to the empirical data collected.

The critique of the pure reason is a program whose database is formed by all the pure reasons, and per pure reason, at least fourteen files, one per rational check or comparison, practically all the rational checks and comparisons are already developed in the Modelling System, with the only exception of the first rational check.

The importance of, in the second stage of the critique of the pure reason, reckoning the frequency of mistakes made when deductive programs wrongly assigned a pure reason to a combination of data in the rational contrastation process itself, as the first rational check, plays a key role in the development of a stronger attributional method. 

If in the critique of the pure reason, is identified any pure reason on the list of pure reasons, whose empirical probability of wrong rational hypotheses, is equal to or greater than a critical reason, that or those pure reasons must be investigated to reformulate the pure reason/s in order to increase its/their accuracy.

What the file related to the first check in every pure reason is going to reckon, is how many times a deductive program assigns the incorrect pure reason to some combination of data, and if the frequency is equal to or greater than a critical reason.

And while the critique of the pure reason is going to control the accuracy of every single pure reason on the list of pure reasons, at the same time, the critique of the deductive programs is going to asses the accuracy of the attributional method working in the deductive programs, so that or those deductive programs with the higher frequency of wrong attributions, should be fixed, analysing which deductive program has the high frequency or wrong attributions, and in which pure reason the wrong attributions are committed more frequently, contrasting the common mathematical structure of that kind of data in which the deductive program has more wrong attributions, and why wrongly the deductive program assigned this pure reason to that data wrongly.

Similar to the critique of pure reason, the critique of the deductive programs must have one file per rational check and rational comparison, counting the frequency of wrong rational hypotheses made by every deductive program found in every rational check and rational comparison.

With the right protocol to analyse the mathematical structure behind some data, the automation of any process to discover mathematical errors made by any deductive program could be easy, and how to fix deductive programs, only observing their more common mistakes, could be automatable.

In fact, what a deductive program must do is to identify the mathematical structure behind any data, assigning the correct pure reason. If this is possible, the inverse process to fix a deductive program is possible too: the analysis of common errors in its attributions, to fix the problem in the program.

The critique of pure reason, as well as the critique of deductive programs, are going to be really important, along with the Learning System, to make decisions about how to improve the Global Artificial Intelligence. And once these decisions are authorised by the Decisional System, these decisions could be put into practice, within the Application System, by Artificial Engineering, which consists of: the Artificial Designer of Intelligence, and the Intelligent Robotic Mechanic.

Rubén García Pedraza, 15th of July of 2018, London
Reviewed 27 August 2019 Madrid

Reviewed 21 August 2023 Madrid

Reviewed 11 May 2025, London, Leytostone

imposiblenever@gmail.com