The database in Specific Artificial Intelligence for Artificial Research By Deduction

The database in any Specific Artificial Intelligence for Artificial Research By Deduction, must always be a matrix, whose Application, as the first stage in this Specific Artificial Intelligence, consists only of all the necessary factors for the research in any specific synthetic science, specific synthetic academic field, or within a specific interdisciplinary or multidisciplinary study treated as a specific synthetic academic field, or any other activity.

Once the first stage of the Application is finished, in the second stage, the replication stage, the matrix will be filled with the flow of measurements obtained by robotic devices. But this second stage is only after the total completion of the first stage: the construction of the database as a matrix.

In this post, I will develop some examples for the construction of a specific matrix for Specific Artificial Intelligence for Artificial Research by Deduction, taking as examples possible research using this technology in tectonics, climatology, transport, and gravity.

For the formation of this database, something really important, in the core of Impossible Probability, is the consideration of at least two types of information from the synthetic world: direct punctuations and frequencies.

Depending on the nature of the information, direct punctuations or frequency, the way in which in the second stage of replication the information is going to be treated is different, except by the use of the Second Method of Impossible Probability, where all information is transformed into empirical probabilities.

However, the Second Method of Impossible Probability should be treated only as what it is, a Second Method after the first one: the traditional statistics and the traditional probability. What is really important, regardless of what kind of methodology is used in the second stage of replication, is to understand the real meaning of the database as a matrix in the first stage of application in any Specific Artificial Intelligence for Artificial Research by Deduction.

Some specific matrices for some specific synthetic sciences, synthetic academic fields, or activities, are going to be integrated by databases whose factors are going to be measured only in direct punctuations, other databases by only frequencies, but other data ases are going to integrate into the same database factors whose measurement is made by direct punctuations and others by frequencies.

The ideal in Impossible Probability working on Artificial Intelligence, is the possibility of the construction of databases where, regardless of what kind of information is gathered, direct punctuations or/and frequencies, all information must be integrated in the same database, and should be treated using the same statistical and probabilistic methods.

Starting with some examples for the elaboration of a specific matrix for a Specific Artificial Intelligence for Artificial Research by Deduction, the first example to develop will be applied in tectonics.

If we have to develop a specific matrix only for tectonics, something to consider is the fact that some tectonic factors measured by robotic devices will be measured as direct punctuations while others as frequencies.

For instance, if we want to measure the geological temperature at different locations in the terrestrial geological structure, the temperature is a kind of information measured as direct punctuation.

The way in which it is possible to work with flows of direct punctuations of temperature around the world is the following, every single thermometer considered as a factor for the measurement, will be defined in quantitative terms indicating exact location in terms of latitude, longitude, and Depth  (below the sea level, in the sea or the ocean) or height (above the sea level, in continents and islands). So if we have thousands of thousands of thermometers at different depths or heights at different locations, we will have a temperature map of the planet directly from thermometers located in these positions. At the same time, via artificial satellite is possible to have another possible map of terrestrial temperature, indicating the temperature estimated for every single point defined in terms of latitude, longitude, or even depth or height.

In the same way that every thermometer, or every point of temperature by artificial satellite is a single factor to include in this specific matrix, which are going to give a flow of direct punctuations of temperature for each location as a factor in this specific matrix, another one is the measurement of any quake or any phenomenon in which any surface suffers a trembling in any part of the world, even the most menial, taking as direct punctuations their intensity.

But at the same time, using taxonomies of possible tectonic phenomena such as earthquakes, tsunamis, and volcanoes, as well as any other, differentiating categories of each type of possible phenomenon depending on their intensity or any other quantitative difference, in the same matrix is possible to have an updated measurement of the frequency in which each one happens, measuring their frequency across the world and their frequency in every single point of the world.

Nowadays, there are many agencies specialised in this kind of investigation with very powerful measurement instruments. One of them for instance, is the United States Geological Survey.

In fact, the work for the construction of a database with the shape of a matrix for Specific Artificial Intelligence for Artificial Research by Deduction in tectonics is not very difficult with the current organisations working in this synthetic science. I have mentioned the United States Geological Survey because maybe is one of the most famous organisations in this field across the world, but in Europe, Russia, and China, there are similar organisations, with their own instruments of measurement and their own databases.

Having as databases the ones that these organizations can provide, the only thing that a team in Artificial Intelligence must do for the construction of a Specific Artificial Intelligence for Artificial Research by Deduction in tectonics is only to have a look their databases, to check how they are organised, try to integrate absolutely all of them if possible, or at least as many as possible, in only one, and practically the first stage for the construction of a Specific Artificial Intelligence for Artificial Research by Deduction in Tectonics is done.

In the same database must be integrated absolutely every type of information, in direct punctuations, such as geological temperature or intensity of quakes, and every kind of information in frequencies, such as the frequency in which any type of geological phenomenon happens: earthquakes, tsunamis, volcanoes, differentiating for each one different category according to their intensity, having the frequency of each of them in each possible location where the measurements are made.

All databases, of direct punctuations and frequencies, integrated in only one, allow the formation of empirical hypotheses, taking as possible stochastic relation any possible relation between any factor in the same database, possible stochastic relation that after rational contrastation, if it is rational, will be an object of single and comprehensive modelling.

In the same way that a specific matrix for a Specific Artificial Intelligence for Artificial Research by Deduction in tectonics is easy to prepare, given the current databases of tectonics across the world thanks to the incredible work made by scientists in different organizations at the national or international level, could be made any other specific matrix, for any other purpose, taking the current databases from any other national or international agency, as a good resource to start the creation of any other Specific Artificial Intelligence for Artificial Research by Deduction, in any other synthetic science, synthetic academic field, or activity, such as oceanography, population, economy, education (for instance the global databases in the economy by the Organisation for the Economic, Co-operation, Development), human rights (databases provided by United Nations),  climatology, and many more.

The application, by Artificial Intelligence teams, with the assistance of, in a future much nearer than we think, Specific Artificial Intelligence for Artificial Engineering, such as the Artificial Designer of Intelligence and the Intelligence Mechanic Robotic, are going to be the first experiments about how to apply the Artificial Research by Deduction in different specific synthetic sciences, synthetic academic fields, or activities, that after successful results, once the first gigantic global database will be ready, these previous experiments will facilitate the transformation of this first gigantic database in a global matrix.

The construction of Specific Artificial Intelligences for Artificial Research, by Application or Deduction, and the application of Artificial Research by Deduction in Global Artificial Intelligence, will facilitate and accelerate the process of automation of scientific research.

At the same time, the first models of collaboration between Artificial Research by Application and Deduction are going to appear, as long as the completion of the unification process of Specific Artificial Intelligences for Artificial Research by Application in a unified database, which will end up finally being integrated in the global matrix.

The next example of a specific matrix that I will develop is about climatology.  In the construction of a specific matrix in climatology, for Specific Artificial Intelligence for Artificial Research by Deduction in climatology, the same process, in absolutely only one database, the inclusion of absolutely everything related to climatology, regardless of whether the information is gathered as direct punctuations or frequencies.

For instance, a) the definition of every thermometer as a factor, across the world, defined the factor in quantitative terms of latitude, longitude, and altitude, b) the definition of terrestrial points as factors where to meassure the speed of the wind in terms of latitude, longitude and altitude, c) the definition of any point as a factor for the measurement of how many litres per square is raining or snowing, or any other kind of precipitation defining every location as a factor in terms of latitude, longitude, altitude.

The definition of any single point of the planet as a factor of measurement where is going to be measured any climatologic phenomenon: breeze, will, blizzard, drizzling, rain, hail, snow, storm, cyclone, tornado, hurricane, or any other, even the consideration as climatologic phenomenon the possible effects of solar storms in the terrestrial climatology, or even the consideration as a climatologic phenomenon the entrance of any meteorite in our atmosphere, every single phenomenon that happens in the atmosphere should be considered as possible climatologic phenomenon. Defining every single point where these measurements are taken in quantitative terms of latitude, longitude, and altitude, including in the same database, the measurements by direct punctuation or frequency.

In the same database, direct punctuations of temperature, speed of the wind, precipitation, among many others, for sure, and frequencies of breeze, will, blizzard, drizzling, rain, hail, snow, storm, cyclone, tornado, hurricane, or any other, differentiating categories of each type of possible phenomenon depending on their intensity or any other quantitative difference, where is going to be measured, in the second state, their frequency across the world and their frequency in every single point of the world.

This specific database for climatology follows the same structure as the specific database for tectonics.

 In absolutely only one database, the inclusion of absolutely all the information of a specific synthetic science, discipline or activity, regardless of how this information is measured, in direct punctuations or frequencies, and having absolutely all the information in only one database, in the second stage of replication, the Specific Artificial Intelligence for Artificial Research by Deduction should be able to carry on empirical hypothesis, that after rational contrastation if accepted must be an object of single and comprehensive models.

Every stage and step in this long process should be entirely automated. The Specific Artificial Intelligence itself should be able to do this job by itself, without human intervention.

Nowadays, there are lots of organisations working in climatic studies from the national level to the international level, one of the most important being the Intergovernmental Panel on Climate Change, and across the entire world, there are thousands and thousands of centres, laboratories, universities and institutions doing all kinds of climatic measurement,

An Artificial Intelligence team having access to these databases, and integrating into only one database all possible information, regardless of how the information is taken, in direct punctuations or frequencies, can create a specific matrix of climatology, that is inserted in a Specific Artificial Intelligence for Artificial Research by Deduction in climatology, automatizes all the scientific research process in this area, doing by itself all the necessary scientific work.

The main benefit that these excellent designs of Artificial Research, by Application and Deduction, are going to give to the entire humanity is the possibility of the production of a cheaper and faster science, which will accelerate scientific progress. And finally, these first models in Specific Artificial Intelligence for Artificial Research, by Application or Deduction, applied to absolutely all databases across the world (for all countries, in all sciences, disciplines, and activities) are going to make really easy the creation of a Global Artificial Intelligence, and within it, a global matrix, working 24 hours a day, 7 days a week, in the production of scientific knowledge, that will make easy the complete automatization of any other activity, especially the automation of the economy. Actually, this is the early beginning of something much bigger, the creation of a science and technology beyond human understanding.

Continuing with the range of examples that I had planned for the explanation of how to make a specific matrix for Specific Artificial Intelligence by Deduction, the next example is about transport.

This topic is not itself a synthetic science. It is a kind of interdisciplinary or multidisciplinary study of a specific activity treated as a synthetic academic field. The possible factors to choose depend on the specific goal that the Artificial Intelligence team intends to achieve through the creation of this Specific Artificial Intelligence for Artificial Research by Deduction in transport.

The following example is the construction of a matrix designed to determine how many types of fuels are used, how much fuel, for everyone, is used, for how many travellers, and for how many hours, in total or per person.

This specific matrix integrates factors measured in direct punctuations and factors measured in frequency, and the possible factors are: 1) every single kind of transport, motorcycles, cars, taxis, buses, lorries, trains, airplane, boats, ships, differentiating every category, for instance one category for every kind of car, or even every brand or car maker, 2) what kind of fuel uses every single category,  and specifically for each continent, country, province, city, town, and small village, international companies, national branches of international companies, national companies, small business ,or for particulars, families, or every particular person  2) how many of them are in total around the globe, and specifically for each continent, country, province, city, town, and small village, international companies, national branches of international companies, national companies, small business ,or for particulars, families, or every particular person  3) the consume of every kind of fuel, differentiating among continents, countries, provinces, and if possible even cities, towns, and small villages, international companies, national branches of international companies, national companies, small business, or for particulars, families, or every particular person  4) the frequency in which this transport are used around the globe, and each continent, country, province, city, town, and small village, international companies, national branches of international companies, national companies, small business, or for particulars, families, or every particular person , 5) the hours in which they are used around the globe, and each continent, country, province, city, town, and small village, international companies, national branches of international companies, national companies, small business, or for particulars, families, or every particular person, 6) the purposes in which they are use, differentiating categories for every kind of job, laboral sector, leisure, as well as any possible other, around the globe, and each continent, country, province, city, town, and small village, international companies, national branches of international companies, national companies, small business, or for particulars, families, or every particular person  .

Similar databases should be developed by the R&D departments of fuel and automotive companies, ship makers, etc... the only thing to do for the elaboration of a specific matrix in this area, is to collect all the databases, independently if their factors are measured by direct punctuations or frequencies, in order that in the second stage of replication, the Artificial Intelligence, after the identification of possible stochastic relations, if accepted as rational, makes single and comprehensive models.

Finally, the last example to bring up here, is gravity, a Specific Artificial Intelligence for Artificial Research by Deduction in gravity, whose database is a specific matrix where all the factors are only locations described in quantitative terms of latitude, longitude, depth or altitude, so later on in the second stage by robotic devices to fill in the matrix the measurements obtained about the intensity of gravity in each point. The main purpose of this Specific Artificial Intelligence would be the identification of any possible anomaly in the flow of gravity on Earth.

But much further than this, having such a kind of Specific Artificial Intelligence, the possibility that across the universe, by spaceships, artificial satellites, and telescopes as well as robots on other planets such as Mars, all of them giving permanently a flow of data to this Specific Artificial Intelligence, and defining in quantitative terms any point of the universe from the information comes, the possibility to study any possible anomaly in the gravity of any galaxy, star, black hole, red dwarf, planet, satellite, asteroid, comet, meteorite across the universe.

Databases like this one are currently available in national space agencies such as NASA, EAS, ROSCOMOS, CNSA, among others. The only thing that an Artificial Intelligence team has to do is to integrate all databases about gravity from the Earth, and across the universe, depending on the projects, planetary or the universe, integrating all databases in only one, defining every point of the Earth or the universe to study in quantitative terms.

The formation of any specific matrix for any specific synthetic science or any synthetic academic field for any Specific Artificial Intelligence for Artificial Research by Deduction is always the same process: the definition of any factor to study in quantitative terms, nothing else. After the completion of this first stage, when the specific matrix is ready, then the second stage of replication.

Once the measurements are taken by robotic devices, filling permanently in the matrix with the measurements, as a flow of data, then the Artificial Intelligence must work permanently without time off, 24 hours a day, 7 days a week, identifying possible stochastic relations among the Flow of data in the matrix, stochastic relations treated as a possible empirical hypothesis, in order to rationally criticize, and only if rational, the elaboration of a single virtual model of only those rational hypothesis, to integrate in a comprehensive virtual model.

The way in which this artificial intelligence is going to experiment with cyclic auto-replications, the third stage of any Artificial Intelligence, among other auto-improvements and auto-enhancements, is through the auto-improvements in the comprehensive virtual model at any time that is made any single virtual model.

After the elaboration of any single virtual model, if the empirical hypothesis has been accepted as rational, the single virtual model of a rational stochastic relation must be included in the comprehensive virtual model of this Artificial Intelligence, where finally, the Artificial Intelligence integrates all single virtual models in only one comprehensive virtual model.

Each time a stochastic relation is accepted as a rational hypothesis, the Specific Artificial Intelligence will generate a new single virtual model. This model is then integrated into the comprehensive virtual model, improving it automatically.

The most important thing in the development of Specific Artificial Intelligence for Artificial Research by Deduction in any synthetic science, synthetic academic field, or activity, is the fact that, in reality, they are the first experiments about how this technology can work, and be improved and enhanced in future models, being the objective the construction of a global matrix, for a Global Artificial Intelligence, able to carry on studies at global level, not only in one specific synthetic science, only one specific synthetic academic field, or only one activity, the Global Artificial Intelligence using Artificial Research by Deduction, after the completion of the global matrix, must be able to carry on all kind of studies, identifying all possible stochastic relations, around the globe or beyond, the universe, carrying on all kind of rational contrast, in order that, with absolutely all the rational hypothesis, the construction of a global virtual model.

 Rubén García Pedraza, London 15th of February of 2018
Reviewed 6 August 2019. Madrid

Reviewed 8 August 2023. Madrid

Reviewed 3 May 2025, London, Leytostone

Replication processes in Artificial Research by Application

Replication processes are all those designed to imitate human skills, physical or psychological, by robotics or Artificial Intelligence, distinguishing in Impossible Probability between Specific Artificial Intelligence and Global Artificial Intelligence.

An example of physical replication, is all robotic arms (guided by a Specific Artificial Intelligence) operate in the reality (in the same way that human arms allow us to do any action ordered by our brain), such as robotic arms imitating human skills guided by a Specific Artificial Intelligence in the industry or the space exploration.

An example of psychological replication, is any process involved in artificial psychology, such as artificial learning or artificial research, among others, from the automation of the economy to the automation of lots of processes in security or surveillance.

Actually, robotics is specialized in the robotic replication of all kinds of human physical skills, as well as the replication of animal or insect physical skills, such as those models which tried to imitate animal movements over four or six legs, or how some insects fly or creep. However, the most important physical skills required for the automation of the economy, or any other human activity, are the replication of human physical skills.

While the research in robotics is focused on the replication of physical skills, mostly human, Artificial Intelligence is focused on the replication of human psychological skills, artificial psychology.

A perfect android would be a perfect combination of the best robotic replications of all human physical skills and the best Specific Artificial Intelligence for the best replication of human psychology.

In Impossible Probability is important the distinction between Global Artificial Intelligence and Specific Artificial Intelligence.  A Global Artificial Intelligence studies and works globally in all kinds of activities and scientific subjects. While Specific Artificial Intelligence is focused only on one specific activity (for instance, one economic activity) or one specific subject (for instance, one scientific science or academic field).

The Global Artificial Intelligence should be able to do research and make decisions globally across all scientific subjects and academic fields, be able to do multi-disciplinary and inter-disciplinary studies automatically, develop automatic multi-causal virtual models, integrate rational hypotheses from all sciences and academic fields, be able at the same time to manage all human activities, from economy, security, and surveillance, among many others.

Specific Artificial Intelligence is designed for only one activity or only one scientific subject or academic field. For instance, a Specific Artificial Intelligence for the extraction process of mineral resources on Earth or other planets, identifying minerals to extract, and managing the extraction robotically, or a Specific Artificial Intelligence for Artificial Research by Application specialised in medical problems, curing people across the whole globe, or even, if they would exist, human colonies in exoplanets across the universe.

Having a clear idea about the concept of replication, distinguishing robotic replications and replications in Artificial Intelligence, and distinguishing between Global and Specific, it is time to develop the main core of this post, the replication processes involved in a Specific Artificial Intelligence for Artificial Research by Application.

Any Specific Artificial Intelligence for Artificial Research by Application, as well as any other Artificial Intelligence, Global or Specific, is going to be developed following the three stages, within the Impossible Probability theory, set out in other posts: application, replication, and auto-replication.

The application normally is going to consist of a database, whose main characteristics in by Application at a specific level have been developed in the last post of this blog “The database in the Artificial Research by Application”.

The second stage, replication, consists of all the necessary replications, of human psychological processes, that, working all together over the application, the database, is going to be able to develop or achieve the main purpose for what the Specific Artificial Intelligence has been designed, in this case, the main purpose is the achievement of scientific researches in that synthetic science, synthetic academic field, or activity, where Artificial Research by Application could give good results (in other cases could be better the use of Artificial Research by Deduction, which is going to be developed in other posts).

Finally, in the third stage, auto-replication, Artificial Intelligence should be able to improve and enhance itself, for instance, improvements in its own database by itself, without human intervention.

In a previous post on this blog was developed the main characteristics of the database, the application itself, in the Artificial Research by Application, the first stage in this Specific Artificial Intelligence. Continuing with the development of this model of Specific Artificial Intelligence for artificial research, in this post, I will develop the main characteristics of its second stage, replication processes in Artificial Research by Application.

For the development of the second stage in Artificial Research by Application, in any synthetic science, synthetic academic field,  or activity, is necessary to have a clear idea about what is robotic replication and research replication. A clear idea about, which replications are robotics, and which ones are replications of Artificial Intelligence.

The replications that are going to be required in the second stage of any Artificial Research by Application are:

- Robotic replications in order to obtain measurements from real objects (the robotic replication of all human skills involved in any measurement), measurements that later are sent to the Specific Artificial Intelligence

- Comparison by the Specific Artificial Intelligence between the measurements from the real object and the categories in the application, the database. This comparison must end up giving a percentage of similarity between the measurements taken from the real object and the quantitative descriptions of each category.

- Selection by the Specific Artificial Intelligence of all those categories within the database with a high percentage of similarity with the measurements taken from the real object.

- The Specific Artificial Intelligence set up these categories as possible empirical hypothesis about the very nature of the real object.

- According to the nature of each possible category now as an empirical hypothesis, the Specific Artificial Intelligence automatically proceed to gather samples from the reality ordering to the robotic replications the formation of such samples.

- By Robotic replications, the samples are gathered according to the orders received from the Specific Artificial Intelligence.

- Robotic replications measure any factor in the samples according to each category as a possible empirical hypothesis, and the measurements later are sent to the Specific Artificial Intelligence.

- According to the nature of its synthetic science, synthetic academic field, or activity, the Specific Artificial Intelligence chooses the best methods in order to critically contrast the hypothesis or group of hypotheses. For instance, in Specific Artificial Intelligence for Artificial Research by Application on medical problems, the samples that the robots are going to take could be samples of corporal temperature, blood, DNA, or any other. According to the synthetic science, synthetic academic field, or activity, and the nature of those empirical hypotheses to contrast, the Specific Artificial Intelligence chooses the best statistic methods forthe contrastation of empirical hypothesis, which in Impossible Probability is the rational criticism.

- In synthetic science, synthetic academic field, or activity, in which this Specific Artificial Intelligence is working, is a science, academic field, or activity, which uses statistical and stochastic methods, the Specific Artificial Intelligence proceed to criticize rationally the empirical information obtained from the samples in order to make rational decisions. So according to the nature of the categories selected as empirical hypotheses, the Specific Artificial Intelligence chooses what statistical method of rational contrast would be the best one for each empirical hypothesis.

- According to each statistical method for the rational criticism of each empirical hypothesis, the Specific Artificial Intelligence chooses a critical reason.

- The Specific Artificial Intelligence does all the necessary calculations in order to know if the empirical value obtained through the statistical method of rational contrast, is equal or superior to the critical reason.

- If in one or more than one empirical hypothesis, categories were chosen from the database, the empirical value from the samples is equal or superior to the critical reason, that one category as an empirical hypothesis or those ones categories as empirical hypotheses, is or are selected by the Specific Artificial Intelligence as rational hypothesis about the very nature of the real object.

- In Impossible Probability, one or more than one hypothesis makes or make a theory, and one theory or more theories is or are able to generate a model. Because the purpose of a Specific Artificial Intelligence is not to write a scientific book, publish in a scientific journal, give a lecture at a university, or a conference at a scientific congress, the formation of theory is not really important in artificial research. In artificial research, what is going to be really important is, once an Artificial Intelligence, Global or Specific, has a rational hypothesis or a core of rational hypothesis, over the rational hypothesis, the formation of virtual models that could replicate real objects as virtual simulations, made by the Specific Artificial Intelligence for Artificial Research itself, either by Application or by Deduction. 

In Global Artificial Intelligence would be the whole replication of the synthetic world in a global virtual model. The global replication of the whole synthetic world in a global virtual model could be made by a global matrix, in collaboration with the contributions of specific models, such as the models that could be made by Specific Artificial Intelligence for Artificial Research, by Application or Deduction, integrated within the Global Artificial Intelligence. 

For that reason, the creation of virtual models from the synthetic world is really important because by the time all Specific Artificial Intelligence can be integrated into the Global Artificial Intelligence, within the global virtual model could also be integrated specific virtual models, such as specific virtual models of human beings or any other real object modelling by any Specific Artificial Intelligence. Actually, every specific virtual model, made by every Specific Artificial Intelligence, would be a virtual replication as a virtual simulation of a specific synthetic reality. And a global virtual model, made by the Global Artificial Intelligence, would be the virtual replication as a virtual simulation of the whole reality.

- In case the empirical value from the samples is inferior to the critical reason, the empirical hypothesis are discarded, and taken the measurements from the samples, this new kind of sample becomes a new category in the database. The Specific Artificial Intelligence set up a new category in the database of its own application, the category that is going to be described in quantitative terms with the empirical measurements taken from the samples. This process of inclusion of a new category in the database by the Specific Artificial Intelligence itself, is an act of auto-replication, in the sense that, without any human intervention, the Specific Artificial Intelligence could improve by itself the database.

- Once the new category has been set up within the database in the application, finally taken this new category provisionally as a rational hypothesis, the creation of a virtual model of this new category.

In other posts, I will develop the creation of specific virtual models and global virtual models, from the reality. But for now, what is really important is to have in mind the idea that, through Artificial Research by Application, in a Specific Artificial Intelligence, alone or integrated into a Global Artificial Intelligence, and through Artificial Research by Deduction, in a Specific or Global Artificial Intelligence, the result of these investigations will be the creation of complete replication as a simulation of this world in a virtual world, through the creation of specific virtual models, and finally the creation of a global virtual model.

In this post, what I have developed is only the most essential steps in the second stage of replication for any Specific Artificial Intelligence for Artificial Research by Application in a synthetic science or synthetic academic field, where the most important scientific methods are statistical or stochastical.

But in general, for any other synthetic science or synthetic field, where the statistical or stochastic methods are not relevant, most of the steps described for this second stage are practically the same. The only thing that changes is the fact that in those steps where the operations made by the Specific Artificial Intelligence are not statistics or stochastics, the application of alternative methods in the second stage would need a very careful description of what operation the Specific Artificial Intelligence must do in every single step, following the alternative method, in order to make a decision about the acceptance or not of the empirical hypothesis, in order to make further decisions upon the results, and further virtual models.

Regardless of what kind of scientific method the Specific Artificial Intelligence could use in order to make a decision if the hypothesis or group of hypotheses is or are accepted, then the creation of virtual models. If not, the creation of a new category within the database, including the measurements, as quantitative descriptions for the new category, from the samples taken from the new real object, and modelling a new virtual model based on this new category as a new, at the same time universally and provisionally, rational hypothesis.

Finally, saying that this general model that I have set up in this post regarding a possible model of replication processes in Artificial Research by Application is a model that could be replicated in any synthetic science or synthetic academic field, where the use of a Specific Artificial Intelligence for Artificial Research by Application could be suitable.

For other synthetic sciences, synthetic academic fields, or activities, in which much more than the formation of hypothesis over taxonomies, the purpose is the discovery of correlations, probable causes and effects, and the study of stochastic relations in general, the Specific Artificial Intelligence for artificial research in this of investigation, should be designed through Artificial Research by Deduction, what is no other thing than the replication of all processes involved in statistic or stochastic deduction of empirical hypothesis, that later on in the rational contrast are going to criticize rationally.

In any case, any Specific Artificial Intelligence for Artificial Research, either by Application or by Deduction, is an Specific Artificial Intelligence that should be able to work with thousands and thousands of robotic devices across the Earth, and beyond, across the universe, giving the chance to do thousands and thousands of rational contrastations at the same time, making at the same time thousands and thousands of decisions, creating at the same time thousands and thousands of specific virtual models, that by the time the integration process off all Specific Artificial Intelligence into the Global Artificial Intelligence is done, could give the opportunity to integrate in a single virtual global model thousands and thousands of specific virtual models, at the same time that each Specific Artificial Intelligence for Artificial Research, either by Application or by Deduction, as well as the Global Artificial Intelligence itself, can auto-replicate themselves automatically, thousands and thousands of times, integrating new discoveries and new virtual models.

Rubén García Pedraza, London 11th of February of 2018
Reviewed 03 August 2019, Madrid

Reviewed 8 August 2023, Madrid

Reviewed 3 May 2025, London, Leytostone

The database in Artificial Research by Application

A database is a collection of information for some particular purpose or over some particular field. In statistics, every single category or option must be defined or limited in quantitative terms, given an exact definition of what information we need to measure, and later, the results of these measurements must be added to the database.

In Impossible Probability the measurement of any quality of a subject or option is the transformation of a qualitative property into a factor of mathematical operations, which can be converted into positive data, for the description,  inference, or prediction of the phenomena studied in synthetic sciences.

The definition of any data in quantitative terms is a warranty as well, which is defined in a positive way. Data is positive when its acceptance is independent of any ideological or political difference between different schools or paradigms.

Once we have a general definition of the database through the theory of Impossible Probability, it is time to give a definition of the database in the Artificial Research by Application, that, generally speaking, would be a collection of: information, taxonomies, classifications, files, categorizations, events, facts, phenomenon, characteristics of individuals and populations (physically, behavioural, psychologically), or any other thing, even any tool to use later; necessary in any artificial research processes made by the Artificial Research by Application, which through the information collected in its database, is going to be able to automatize the formation of empirical hypothesis within the synthetic science or synthetic academic field for what it has been created, and able therefore to criticize rationally the empirical hypothesis in order to make further rational decisions.

If the application finds some category, event, or phenomenon without a high percentage of similarity with those ones stored in the database, this new one must then be integrated into the database as a new one.

This process of including new categories, events, or phenomena in the database constitutes an auto-replication process, as the application can improve its components—particularly the database—without human intervention.

As first stage in the formation process of any Artificial Intelligence, either specific or global, for artificial research or any other purpose, a good definition of the concept of database is necessary according to the purpose for which it is going to be designed.

In order to have a clear idea about what kind of database is going to be necessary in Specific Artificial Intelligence for Artificial Research by Application, firstly is important to clarify what different models of database are going to be developed, taking the theory of Impossible Probability as a theoretical model, applied to Artificial Intelligence, Specific or Global. And among all possible databases, the exact purpose of the database in Specific Artificial Intelligence for Artificial Research by Application.

In Impossible Probability is necessary to distinguish, at least, among these models of databases:

- Database in Artificial Research by Application in a Specific Artificial Intelligence. In those Specific Artificial Intelligences for artificial research in synthetic sciences or synthetic academic fields where the artificial research is done by Artificial Research by Application, the database should include all information, data, taxonomies, classifications, files, categorizations, events, facts, phenomena, or characteristics of individuals or populations, or any other thing, even, tools if its necessary, that are going to be needed in the investigations with this technology. This is the model developed in this post.

- A unified database of Artificial Research by Application. In the future, after the completion of the unification process of all Specific Artificial Intelligence for Artificial Research by Application into a Global Artificial Intelligence. Once the creation of a Global Artificial Intelligence has finished the completion of a global database, in addition to this global database it is going to be necessary the process of integration of the rest of specific databases of the rest of Specific Artificial Intelligences for artificial research in synthetic sciences and synthetic academic fields, into the GlobalArtificial Intelligence. This integration process should have different phases. In the first one the unification of all Specific Artificial Intelligences for ArtificialResearch by Application, and after that, the integration of all of them into the Global Artificial Intelligence. The unification process should finish with the integration of all these specific databases by application in only one, a unified database of Artificial Research by Application. Upon it, all the Specific Artificial Intelligences for Artificial Research by Application, from any synthetic science or synthetic academic field, could work together on only one unified database for Artificial Research by Application, the Unified Application. All Specific Artificial Intelligences for Artificial Research by Application, in any synthetic science or synthetic field, could match the measurements taken from real objects with the categories, events, and phenomena included in the unified database, forming and contrasting hypotheses at the same time from the unified database. And in case a new category, event, or phenomenon should be included, introducing improvements across the unified database at the same time. One unified database for all Specific Artificial Intelligence for Artificial Research by Application, whose hypothesis and decisions could automatically be integrated into the Global Artificial Intelligence.

- The database of Specific Artificial Intelligence for Artificial Research by Deduction in any synthetic science or synthetic academic field. In this case, the database is going to be a matrix, where each Specific Artificial Intelligence for Artificial Research by Deduction of each synthetic science or academic field must have its own matrix. The matrix should be formed by the definition of every factor, subject, option, category or any key point relevant to the research, that later on, in the second stage, the replication stage, is going to be measured constantly, receiving a flow of continuous measurements at any time. So, in the second stage, replication, this Specific Artificial Intelligence for Artificial Research by Deduction would fill directly the matrix with the flow of measurements related to every factor, subject, option, category, etc., storing all the information in the memory. And upon the measurements, by statistical methods, the automatic identification of high levels of correlations, identifying probabilities of cause and effect, and stochastic relations, which could be formulated automatically as a hypothesis, that later could be criticised rationally.

- The database of the Global Artificial Intelligence for Artificial Research by Deduction. A gigantic global database, a global matrix, firstly perhaps over a nation as an experiment that later could be extended over a whole continent, the entire planet, finishing with the inclusion of information that could come from the whole universe. Every single piece of information included must be defined in very exact and quantitative terms, allowing the necessary measurements constantly all the time, getting a flow of measurements at any time, stored continually in the memory, which, by statistics methods, and studying the evolution of the flow, the Global Artificial Intelligence could find high levels of correlations among factors, subjects, options, categories, or probable causes and effects, and stochastic relations. Upon the results, the formation of the empirical hypothesis contrasted later with the critical reason, in order to make further rational decisions.

Among all of these models of database developed under the Artificial Intelligence theory in Impossible Probability, the database object of this post is the first one: the database in Artificial Research by Application in a Specific Artificial Intelligence.

In other posts, I had set out some examples of Artificial Research by Application in Specific Artificial Intelligence for medical problems or astronomy. In this one, I will expose some others for different purposes, focusing on the explanation of how the database in this model of artificial research could work

The first example is applied to mineralogy, and the second one is to the physics of particles.

The first example would be a model of Specific Artificial Intelligence for Artificial Research by Application in Mineralogy. Firstly, the database would be an exact and full taxonomy of all kinds of minerals, rocks, pebbles, and every single kind of mineral, rock, pebbles, would be a category described in quantitative terms: from its possible chemical composition, resistance, hardness, to a definition of the colour in quantitative terms, or any possible other quality described in quantitative terms able to help in the artificial identification of any rock, mineral, pebble, from the reality, the synthetic world.

The description of every mineral, rock, or pebble in the database would be a category (in this case, the subject). Any mineral, rock, or pebble found in the synthetic world, the reality, would be a real object.

In the second stage of Artificial Research by Application, the replication of the research skills necessary for a scientific investigation, given the measurements of any real object, in this case, mineral, rock, or pebble collected from the real world, the Specific Artificial Intelligence could compare the measurements taken from the real object with the quantitative descriptions of every category in the database.

As a result of this comparison, the Artificial Research by Application should give a list of categories with the highest percentage of similarity between their quantitative descriptions and the measurements from the real object, categories as empirical hypotheses about the very nature of the real object taken from reality. Empirical Hypotheses that, if after rational criticism, are true, become rational hypotheses, forming part, at the same time, universally and provisionally, of the rational truth.

In case the real object found in reality, the synthetic world, does not match with any category in the database, the hypothesis must be formulated under the idea that this object belongs to a new category that must be included in the database. This automatic improvement in the database in the Specific Artificial Intelligence for Artificial Research in mineralogy must be considered as an auto-replication, improving its own database. One way, among others, of auto-replication, which means auto-improvement, and in much more developed models of auto-enhancement.

In this first example of the database in a Specific Artificial Intelligence for Artificial Research by Application in mineralogy, as application, the database would be a collection of categories (in this specific example, each category from the database corresponds to each kind of mineral, rock, pebble, taken from the mineral taxonomy). As a second stage of replication, upon the measurements of a real object, the comparison of the empirical measurements from the real object and the quantitative description of every category included in the database: that or those categories or categories with the highest percentage of similarity between its quantitative description with the quantitative measurements from the real object, is the category or are the categories taken as an empirical hypothesis about the very nature of the real object.

Using the same database, within the same application for Artificial Research by Application, the same Specific Artificial Intelligence could work in thousands of locations at the same time.

Thousands of robotic devices specialised in mineralogy, linked all together to the same Specific Artificial Intelligence, with the same Artificial Research by Application in mineralogy, using the same database: in thousands of locations around the Earth, or in space exploration on board of artificial satellites or spaceships, robotic devices specialised in mineralogy working in thousands of planets, satellites, asteroids, or comets, or any other celestial body; could allow us to have a deep knowledge about this specific science beyond Earth and our human limits, and what is really important, reducing constantly the margin of error through decisions more and more rationals.

This Specific Artificial Intelligence, specialised in mineralogy through Artificial Research by Application, could make thousands of thousands of hypotheses at the same time, making thousands of thousands of rational contrasts of hypotheses, using thousands and thousands of robotic devices taking measurements and preparing samples for further rational contrasts and rational decisions, wherever we would like to know the mineral structure of geological formations across the Earth or the entire universe.

And, at any time that any robotic device finds any real object that does not match anything in the database, it could then be possible the automatic inclusion of new discoveries in the database, after rational contrast. New discoveries are available automatically for any other robotic device.

This would mean that thousands of thousands of auto-replications through improvements in the database, adding new categories would be able to be possible at the same time. Under this supposition, the database could be replicated every minute or every second. The increment of knowledge in synthetic sciences and synthetic academic fields, thanks to the automation of scientific research, would give us a very powerful tool in order to have incredible knowledge at a very high speed.

The second example of the database under such a Specific Artificial Intelligence for Artificial Research by Application is its possible application to particle physics.

The first stage of such a Specific Artificial Intelligence would be the creation of a database including a list of categories in quantitative terms for each kind of particle. Secondly, the replication process of all research skills for the formation and rational contrastation of empirical hypotheses: measuring any property of the real object, in this case, the measurement of the properties of any particle, and studying the similarities between empirical measurements from real particles and the quantitative description of every category. Those categories with a high level of similarity between them and a particle or group of particles can be formulated as possible empirical hypotheses about the nature of a particle or group of particles. Once the hypothesis is formulated, over a sample of particles according to the hypothesis, the hypothesis is rationally contrasted, and if it is true, within a rational margin of error, it is rationally accepted.

In case the particle found would have not matched with any category in the database, under the hypothesis that this kind of particle Is a new one, automatically, the artificial research should proceed to the collection of a sample of particles like this one in order to contrast, within a margin of error, that it is a new kind of particle not included yet in the database, so this new one should be included as a new category in the database, describing the new category according to the measurements taken from this new kind of particle as quantitative terms of description. The auto-replication of the database could be done automatically, something really important if thousands of robotic devices in thousands of laboratories and accelerators of particles across the world, or even astrophysics telescopes, would be working with the same database, in the same application of Artificial Research by Application, in the same Specific Artificial Intelligence.

The way in which the database would work is the same as the first example in mineralogy. Given a list of categories in quantitative terms as a database, the replication of rational processes should allow the Artificial Research by Application the possibility that, after the measurement of the properties of a real object, the contrast between the measurements and the categories, and that or those categories with high similarity could be formulated as a possible hypothesis in order to contrast them. In case that after the measurements, the new object does not match with any category, the inclusion of the new object as a new category considering the measurements as the quantitative description of this new category. Inclusion that should be done after further contrastations with samples or particles like this one that could ensure that it is a new kind of category and not a mistake during the measurement process.

It is very important every time that some new real object does not match with any category in the database to discard that this has not happened as a result of a mistake in the measurement process, or for any other reason, such as robotic problems or mechanical problems in the robotic device which has taken the measurements. If gathering samples of real objects like the new one, all of them reveal the same characteristics, within the lowest margin of error, only then, automatically, the new category should be included in the database as a new category. According to the general quantitative properties common to all the samples collected from this specific new object.

Using the same Specific Artificial Intelligence for Artificial Research by Application in any synthetic science or synthetic academic field, thousands of thousands of robotics devices at the same time could work together online. So at the same time, it would be possible that the same Specific Artificial Intelligence for Artificial Research by Application could do as much research simultaneously as robotic devices could work with the same Specific Artificial Intelligence for Artificial Research in any synthetic science or synthetic academic field. What that means is that thousands of thousands of hypotheses could be formulated and rationally contrasted at the same time, making thousands of thousands of further rational decisions at same time, at the very same time that every minute, or every second, or even in a inferior period of time, the database in a Specific Artificial Intelligence for Artificial Research by Application in a synthetic science or synthetic academic field could be auto-replicated by itself through improvements in the database, including new categories based on new real objects found that would have not matched with the current ones.

The importance of the database in Artificial Research by Application is the fact that the same value that the previous bibliographical revision has in any human investigation in order to know what kind of advancements have been made in the field where the investigation is going to be done, in Artificial Research by Application all this previous work is made directly by the database because all new discoveries are already included automatically in the database, and after inclusion, ready and available for any other robotic device working with the same Specific Artificial Intelligence for Artificial Research by Application in any synthetic science or synthetic academic field where this application is useful.

If all discoveries in any synthetic science or synthetic academic field are completely available and ready to be used for other robotic devices, or any human scientists, or even human scientists could share their new discoveries directly into the database, followings investigations in the same synthetic field or synthetic academic field, would be easier to do, because all the new advancements and discoveries are completely ready and available automatically, through an automatic system of auto-replication that could improve, or even enhance, the database, every minute, or even every second.

The database in any specific synthetic science or synthetic academic field could be renewed constantly, including continually, without pause, new discoveries and advancements. The automation of all sciences, starting first with the synthetic sciences, could bring a permanent and automatic scientific revolution.

 Rubén García Pedraza, London 10th of February of 2018
Reviewed 1 August 2019, Madrid

Reviewed 8 August 2023, Madrid

Reviewed 3 May 2025, London, Leytostone