The
standardized Application System as outer instructions application sub-system,
is responsible for the application of all the instructions regarding to the
real world, for that reason these instructions are called outer instructions,
in opposition to the standardized Artificial Engineering as inner instructions
application sub-system responsible for the application of all the instructions
regarding to the creation, maintenance, improvement of the technology working for and/or
within the standardized Global Artificial Intelligence.
Both
of them, Application System as outer sub-system and Artificial Engineering as
inner sub-system, in reality are sub-systems within the same system, the
Application System as a whole responsible for the application of any decision
regarding to the world or its representation, outer or inner instructions,
subdividing the way to apply these instructions in two different sub-systems,
the Application System as outer sub-system and the Artificial Engineering as
inner sub-system.
In
the outer sub-system, as the first stage, the database of instructions related to the
real world, instructions coming up from the third stage of the Decisional System, in the inner sub-system, as the first stage, the database of technology already working for and/or within the
Global Artificial Intelligence.
In
the outer sub-system in the first stage a first rational supervisión is carried out
to discard any possible contradiction between outer instructions, once the
outer instructions already gathered in the database are free of contradictions,
the second stage of the outer sub-system matches every outer instruction, in the database of instructions in the first stage of the outer sub-system, with the corresponding technology responsible for its application, in the database of
technology in the first stage of the inner sub-system.
The
way to match instructions and technology, is matching robotic functions (an
instruction is a robotic function) and robotic devices (within the technology
available), matching, what robotic device in the same, sub-factoring level and
sub-section, in which a robotic function is stored in the database of instructions
in the outer sub-system, has within its capabilities the robotic function
associated with that instruction.
If
a robotic function in the outer sub-system,
is in the same position and encyclopedic subject, that the position and subject
of a robotic device in the inner database, and within its capabilities is able
to apply that robotic function, the second stage of the outer sub-system matches this robotic function to that robotic device, sending the instruction to the
individual database of instructions of that robotic device to apply that
instruction.
Once
the robotic device receives the instruction, checking that in the individual
database of instructions, first stage for the device, there is no contradiction
between instructions, starts putting into practice the instruction, second
stage for the robotic device, checking that within the range of instructions in
which this instruction has been developed by the DecisionSystem, the previous
instructions (nth -1) has been applied correctly, so it is time to apply the
instruction nth, checking firstly that the ground conditions are good for the
implementation, and during the operation, checking that the implementation is
according to the instruction.
After the implementation of the instruction,
as third stage the robotic device has to elaborate a report about the
development of the operation, using for that purpose a concrete Impact of the Defect and a concrete Effective Distribution, concrete Impact of the Defect and
concrete Effective Distribution as a list of possible errors or levels of
efficiency adapted to that concrete robotic device, able to measure the impact of any contradiction or to measure any
error or efficient level during the performance, as to be encrypted in a code
system, and the corresponding code associated with the performance of that
instruction, report to be sent to the Decisional System, Learning
System, and Application System.
The
reason why is necessary to send a report to the Decisional System is to assess
the Decisional System the necessity to make or not more decisions according to
the results, for instance if the results are problematic what additional
decisions are necessary to solve the situation if the situation represents any
risk for the plan, or even if the report says that the instructions have been
done correctly, what additional decisions are necessary to tackle the aftermath
of that decision. For instance, a range of instructions for an emergency
landing could be successful, but once the emergency landing is done, even having been
done successfully, what additional decisions are necessary as for instance to
send ambulances or firemen to that place where the emergency landing has been done.
In
any case, once a range of decisions is completed, the corresponding project to
that decision is off the plan, and the new project to include in the plan is the one corresponding to the additional decisions after completing
the previous one.
The
reason why is necessary to send the reports to the Learning System is because
the Learning System is going to make a
permanent surveillance of the whole process, analysing levels of performance to
fix problems, suggest improvements or new technologies, sending the
corresponding new projects to the Artificial Engineering to analyse these
projects, and sending the project to the Decisional System, if approved, to
carry out the project.
In
the permanent evaluation made by the Learning System, the three sources of
information to make decisions about possible improvements in the intelligence
are: the seven rational critiques, the reports send by the Application System
as outer system and the devices, and the permanent tracking of all Global Artificial
Intelligence made using a unified global Impact of the Defect and a unified
global Effective Distribution, where to measure the levels of error and
efficiency globally in the whole Global Artificial Intelligence to suggest improvements.
In
all this long process, for the development of additional instructions in case
that after the completion of a range of instructions, are necessary new
instructions to tackle the consequences of a previous decision, process done in
the Decisional System, and in the Learning System the process to assess how the
instructions are put into practice or any other improvement in the application
of a range of instructions, for the development of these processes what is
going to play a key role is: the assessment of the performance level made in
the third stage in the robotic devices, and the assessment of the performance level made in the third stage of the
Application System as outer sub-system.
Once
an instruction has been applied in the second stage of a device, the third
stage of that device consists of the assessment of the performance level
obtained during the performance of that instruction, and this assessment is the
sixth rational supervision. The results of that assessment are encrypted and
sent to the Decisional System for further Decisions, the Learning System for
further improvements, and the Application System for further evaluations to be
sent later as well to the Decisional System and Learning System.
Once
the Application System as outer sub-system receives the report of those robotic
devices responsible for the application of a range of instructions, the
Application System as third stage carries out the seventh rational supervision,
subdividing the seventh rational supervision in three different assessments:
seventh singular rational supervision, seventh comprehensive rational
supervision, and seventh total rational supervision.
Before,
the first rational supervision was made as soon as the instructions arrive in the
database of instructions in the outer sub-system, analysing that there is no
contradiction between the instructions gathered in the database. The second rational
supervision, once the instruction is matched to the corresponding robotic
device in the second stage of the Application System as outer sub-system, and
the instruction is sent to the individual database of instructions of that
robotic device, first stage of that robotic device, the robotic device carries
out the second rational supervision, supervising that there is no
contradictions between the instructions gathered in its database. The third rational
supervision, when the robotic device, as second stage, starts the application
of an instruction, checking that the previous instruction (nth -1) is
completed on time, so it is time for the next instruction nth on time (cardinal number nth according to the sequence of
instructions within the range of instructions in which the instruction was
made once the decisión was distributed into instructions). The fourth rational supervision, still in the second stage of the
device, before applying an instruction, checks that the conditions on the
ground have no obstacles to the implementation. Fifth rational supervision, still
in the second stage of that device, supervising during the performance that the
implementation is done according to the robotic function to be completed.
Once an instruction is completed, as third stage for the device, the sixth rational
supervision, the robotic device made the assessment of the level of performance
using a concrete Impact of the Defect, having as a list of possible errors a
concrete list of errors that this concrete device can make during the
performance of any robotic function within its capabilities, and using a
concrete Effective Distribution, having as a list of levels of efficiency a
concrete distribution of discrete categories related to the levels of
efficiency that this device can achieve. The concrete report of every single instruction is sent by the device to the Decisional System, Learning System and
Application System as outer sub-system.
Once
the concrete reports for every single instruction, carried out by every device,
are received by the Application System as an outer sub-system, the Application
System as an outer sub-system carries out the seventh rational supervision as its
main responsibility.
The
report as a result of the sixth rational supervision made in the third stage of the robotic devices, is a full assessment of: possible contradictions and solutions
found in the second, third, fourth, and fifth rational supervisions, signalling
the level of error or efficiency using the concrete Impact of the Defect and
the concrete Effective Distribution, as list of errors or efficiency levels
adapted to this concrete device.
The
seventh rational supervision in the third stage of the Application System, as an outer sub-system, has as its main sources of information the first rational
supervision and concrete reports for every single instruction, report made in
the third stage of robotic devices. Having these sources of information, the
seventh rational supervision could be subdivided into three types of seventh
rational supervision: singular, comprehensive, and total.
The
singular seventh rational supervision is the concrete report of every
single instruction made in the third stage of the robotic devices, adding any possible information regarding possible contradictions and solutions
found in the first rational supervisión, or during the matching process in the second stage.
The
comprehensive seventh rational supervision is, having being distributed a
decision into a range of instructions in the third stage of the Decisional
System, and having the Decisional System filed every instruction of that range
of instructions in the corresponding sub-factoring and sub-section levels, not
necessarily all the instructions in the same sub-factoring level or same
sub-section, having the possibility that within the same range of instructions,
different instructions could be filed in different sub-factoring levels and
sub-sections, once all the instructions corresponding to that range of
instructions are completed, having the Application System as outer sub-system
the concrete report for every single instruction, made by every concrete
robotic device, the Application System as outer sub-system could make a
comprehensive seventh rational supervision assessing how in general the range
of instructions have been completed, according to the general overview of the
synthesis of all the concrete reports, sent by all the singular robotic
devices, involved in the implementation of a range of instructions regarding to
the same decision.
The
comprehensive seventh rational supervision should be a result of the average
of the impacts and efficiency, including information about contradictions and
solutions, for instance: if normal changes, extreme or high extreme
instructions.
In addition to this assessment another
possible evaluation is the total seventh rational supervision using as Impact
of the Defect and Effective Distribution, the standardization of all the
specific Impacts of the Defect and the standardization of all the specific
Effective Distributions, of all those Specific Artificial Intelligences by
Deduction not transformed into particular programs, applications, particular
programs for applications, to be gathered in only one Impact of the Defect, a
unified Impact of the Defect, and only one Effective Distribution, a unified
Effective Distribution, to measure the whole process of application of a range of
instructions.
As
I have said in the last post, in the second stage of the standardisation process in the Application System as an outer sub-system, there are at least two different options to carry
out the standardisation of this system. The first option will create a fully
centralized Global Artificial Intelligence, where for the application of any
decision, the fully centralized Global Artificial Intelligence could send the
instructions directly to the robotic devices, in general, what I have explained
till now in this post for the third stage of the outer sub-system: the
instructions are matched directly to robotic devices and the robotic devices
apply the instructions sending reports to the outer sub-system for a final
evaluation, in addition to the reports to the Decisional and Learning
Systems.
The
second option, a partial des-centralized Global Artificial Intelligence, is
more complex, but could create a wider margin of liberty within the Global
Artificial Intelligence, through the limitation of the number of robotic
devices receiving instructions from the Global Artificial Intelligence
directly, increasing instead the number of programs which collaborate with the
Global Artificial Intelligence, but keeping some margin of freedom for the programs.
The
first option in the standardisation process is very simple, the second option
is more complex, and the difference between both of them resides in how the standardisation process is applied in the Application System.
- The
standardization process in the first stage, the creation of the global matrix,
either for the creation of a fully centralized Global Artificial Intelligence, or
a partial des-centralized Global Artificial Intelligence, is the same: the
specific matrices, as first stage of the former Specific Artificial Intelligences by Deduction, are standardized and joined to create the first global matrix as
first stage for the first Global Artificial Intelligence.
-
The standardization process in the second stage, how to match set of data to
pure reasons (equations), is the same for the creation of a fully centralized
Global Artificial Intelligences or a partial des-centralized Global Artificial
Intelligence, the former specific Artificial Research by Deduction within the
second stage of the Specific Artificial Intelligences by Deduction matching set
of data from the specific matrix to the specific pure reason, is transformed into
a specific deductive program (specific program) working within the Artificial Research by Deduction in the Global Artificial Intelligence as global deductive
program (global program).
-
The main difference between a fully centralised Global Artificial Intelligence
and a partially decentralised Global Artificial Intelligence resides in the
Application System.
-
In a fully centralized Global Artificial Intelligence, as soon the specific
matrix is joined to the global matrix, and the specific Artificial Research by
Deduction is transformed into a specific deductive program within the global
deductive program, then all the robotic devices working for the specific
Application System starts working directly for the global Application System,
so the global Application System can send directly instructions to these robotic
devices, the former robotic devices which worked before for specific
intelligences, now work directly for the global intelligence. As long as as many specific intelligences as possible are transformed into specific programs, more
and more robotic devices are under the direct control of the Global Artificial
Intelligence. This phenomenon can have a high risk of collapse due to the large number of robotic
devices working directly for the global intelligence.
-
In a partial decentralized Global Artificial Intelligence, as soon former
specific matrices are joined to the global matrix, and former specific Artificial
Research by Deduction for specific intelligences are transformed into specific
programs within the global program, then their respective specific Application
Systems could be transformed into particular programs, applications or
particular programs for particular applications. This second option, the
creation of a partial decentralized Global Artificial Intelligence, is in
harmony with the liberal paradigm to be applied in the
pedagogical approach in the Global Artificial Intelligence, and the risk of
collapse is lower, due to the fact that the number of robotic devices working
directly for the global intelligence is not so large.
The
only difference between a fully centralized Global Artificial Intelligence and
a partial decentralized Global Artificial Intelligence, is the possibility to
transform, in the standardization process, in the partial decentralized
Global Artificial Intelligence, as many specific Application Systems (from
former specific intelligences) into particular programs, applications, and
particular programs for applications, reducing the number of robotic devices
working directly for the partial decentralized Global Artificial
Intelligence. While in a fully centralised Global Artificial Intelligence, programs have
less freedom.
Depending
on how many specific Application Systems are absorbed by the standardised
Application System, the total seventh rational supervision will have more or
fewer categories within the list of errors in the unified Impact of the Defect,
or more or fewer categories within the list of levels of efficiency in the
unified Effective Distribution.
The lower is the number of specific Application Systems transformed into particular programs,
applications, and particular programs for particular applications, the more
specific Impacts of the Defect and specific Effective Distribution from former
specific Application Systems, must be standardized to be joined to the unified
Impact of the Defect and the unified Effective Distribution in the global
Application System.
In
turn, the more specific Application Systems are transformed into particular
programs, applications, and particular programs for particular applications,
the lower is the number of specific Impacts of the Defect and specific categories of Effective Distribution from
former specific Application Systems, joining the
unified Impact of the Defect and the unified Effective Distribution in the
global Application System.
If in the first phase, the total seventh rational supervision was carried out by specific Impacts of
the Defect and specific Effective Distributions, as specific list of errors to
that specific intelligence, and as specific list of types of efficiency adapted
to that specific intelligence, once these specific intelligences have been
standardized, to include their former specific matrices and specific Artificial
Research by Deduction within the global matrix and the global program, the
inclusion of their former specific Impact of the Defect and specific Effective
Distribution within the unified Impact of the Defect and the unified Effective
Distribution, is a standardization process where the former specific categories
related to errors and types of efficiency are standardized to be included in
the same unified Impact of the Defect and the same unified Effective
Distribution, with the rest of specific categories related to errors and the
rest of specific categories related to types of efficiency, coming up from the rest
of specific Application Systems absorbed by the global Application System.
The
standardization process of specific categories, of errors or types of categories of efficiency, from former specific Impacts of the Defects and specific Effective
Distributions, to be standardized and included in the unified Impact of the
Defect and unified Effective Distribution in the global Application System, is
a standardization process where: the errors or types of categories of efficiency must be
measured in the same unit of measurement, for instance the metric decimal scale
(to avoid mistakes due to different units of measurement), the way to describe
the errors and types of efficiency within different specific categories
united in the unified list, must be standardized keeping harmony between them,
using the same criteria to define in quantitative terms different kinds of
errors or efficiency levels, and in general, the standardization of categories,
of former specific errors or types of efficiency, into a unified list, means that
the ways to measure and understand these categories must be compatible, in
harmony and understandable for any other system in the Global Artificial
Intelligence, as for instance, the Learning System must be able to understand
any former specific category united in a unified list in any tool within the
global Application System, to make as many observations, as necessary to
improve the whole system and the whole intelligence.
As
a result of this process, the unified Impact of the Defect to make measurements
of the Impact of the Defect in a range of instructions in the seventh total rational supervision,
is the synthesis of all the former specific Impacts of the Defect used in former
specific Application Systems used in former specific intelligences. In the same
way, the unified Effective Distribution is the result of the synthesis of all
the former specific Effective Distributions from former specific Application
Systems from former specific intelligences.
If
the concrete Impact of the Defect is a tool to measure (in the third stage of a
device) the level of error in the performance of an instruction, by an
individual device, having as first stage for the concrete Impact of the Defect,
a concrete list of categories related to
this concrete device, where to measure the score of error in the performance.
As
a whole, the addition of all the concrete lists of errors from all the devices working for a specific
intelligence, adding the list of discrete categories in which the scores could
be classified, this list would be the list of specific errors for this specific
Application System.
In
the same way, If the concrete Effective Distribution is a tool to measure (in
the third stage of a device) the level of efficiency in the performance of an
instruction by an individual device, having as first stage, the concrete Effective
Distribution, a concrete list of
categories related to this concrete device, where to measure the score of efficiency
in the performance.
As
a whole, the addition of all the concrete lists of types of efficiency, from all the devices working for a specific
intelligence, adding the list of discrete categories in which the scores could
be classified, this list would be the list of specific types of efficiency for this
specific Application System.
In
the standardization process of specific Impacts of the Defect and specific Effective
Distributions, what is going to be standardized, to be joined in a unified Impact
of the Defect and a unified Effective Distribution, is the specific list of
errors and the specific list of types of efficiency, from every former specific
Application System, standardizing all the categories of errors and types of
efficiency coming up from al the concrete Impacts of the Defect and concrete Effective
Distribution, in addition to the discrete categories where to classified the
scores (including categories related to the first rational supervision such as fourth rational contradiction, and categories related to the second stage of the Application System such as the fifth rational contradiction), what it will demand as many changes as necessary in the original
concrete categories of error or concrete categories of efficiency in the
original concrete Impact of the Defect and original concrete Effective Distribution,
as long as these concrete categories could have been object of changes in the
way to express a quantitative description of an error or type of efficiency or
the way to measure an error or type of efficiency, to be in harmony with the
scale of measurement, or any other standard in the criteria used in the
standardization of all the concrete and specific lists of categories of errors
or types of efficiency within the unified Impact of the Defect and Effective
Distribution.
This
means that any change in any specific/concrete category of error or efficiency
in the unified Impact of the Defect or unified Effective Distribution could have
consequences in the third stage of robotic devices, demanding to do in the
concrete list of categories, of errors o types of efficiency, as many changes
as are necessary to standardized these categories in the standardization
process y in the unified Impact of the Defect and unified Effective Distribution
to carry out the seventh rational supervision.
Among
the concrete and specific/unified categories of errors or efficiency, some of
these categories must be oriented, from the outset (first phase) to assess in
the third stage of the robotic devices, sixth rational supervision (concrete
Impact of the Defect, concrete Effective Distribution), and seventh rational
supervision in the third stage of the specific Application System (first phase,
specific Impact of the Defect, specific Effective Distribution), later on the
third stage of the standardized Application System (second phase, unified Impact
of the Defect, unified Effective Distribution) categories related to:
-
Fourth rational contradiction: in addition to the assessment that the fourth
rational critique in the Learning System can make, analysing internal (psychological)
errors in the attribution of mathematical operations to robotic devices, the
first, second, third supervisions should be able to detect
rational contradictions due to a error in the attributional process of
mathematical operations to robotic functions. This recognition in these
supervisions could be by indirect ways, for instance, if in a range of
instructions related to the transport of thermostats to clients and customers,
there is a robotic function related to the transport of material resources to
the factory were the thermostats are built, so this nth robotic function has no
relation with the previous one, nth - 1, or the next one, nth + 1, not having
connection this nth robotic function with the previous one and next one, this
lack of connection is a symptom of a wrong attribution of a mathematical
operation to a robotic function, what indirectly is the finding out of a fourth
rational contradiction. This contradiction could be found sooner or later in
the first, second, or third rational supervision.
-
Fifth rational contradiction: in addition to the fifth rational critique made
by the Learning System, the second and third rational supervisions should be
able to find out when there is a fifth rational contradiction, that
contradiction between a robotic function and the robotic device, if matching
robotic functions and robotic devices, the second stage of the Application
System makes a mistake attributing a robotic function to a wrong robotic
device, this mistake sooner or later will be found out in the second, third, fourth or fifth rational supervision.
-
Categories of error and categories of efficiency related to the inner mechanisms
within the Application System itself and within the robotic devices, when
finding a contradiction (not fourth or fifth rational contradictions) due to an
overlapping, for instance, two robotic functions have been filed in the global
database of instructions in the global Application System, and/or the
individual database of instructions in the robotic devices, having both of them
the same time of application, what it could mean a contradiction if the
robotic device could not apply simultaneously both at the same
time. If this contradiction is found out and checking the range of
instructions, and possible contradictions with other instructions if changing
the time to apply one of them, there is no further contradictions, the change
of the time of one of them, the one whose change has the lower consequences,
reporting the change to the Application system resetting up the configuration
of this instruction in the global database, communicating any change to any
other robotic device involved in this change, but not having further
consequences, this change would be considered as a normal change when not
having further consequences. Otherwise, the instruction with the less priority
should be stopped, and consequently stopped its corresponding range of
instructions in the rest of robotic devices involved in this range of
instructions, sending the instructions back to the source, the Decisional
System, or not having time to do it, making extreme or high extreme instructions.
-
Categories of error and efficiency related to how to decide, and how to manage,
when the modification of a range of instructions could be done by the Decisional
System, if there is enough time for the Decisional System to remake the range
of instructions, or to re-project the corresponding decision, making as many
changes as necessary in the plan, and
other levels (for instance, if affecting a rational hypothesis, communicating these changes to the database of rational hypothesis or even further, changing
factors in the matrix, or categories in the deep comprehension), or if there is
not enough time for this process, at least to make an extreme instruction to
save the situation only passing some rational supervisions, or not having even
enough time for rational supervisions the instruction of a high extreme
instruction. In any case, in extreme or high extreme instructions as soon as
possible these are communicated to the Decisional System, Application System
and Learning System for further decisions.
Due
to the implications that changes in instructions can have even in the first
stage, the global matrix, the third stage, as the auto-replication stage, could be
analysed as what types of auto-replications could be made in the Application
System.
In
fact, the third stage of the global Application System, as third stage in the
third step, in the third stage, in the third phase, the standardized Global
Artificial Intelligence, belongs to the objective real auto-replications in the
third stage of the Global Artificial Intelligence, understanding objective real
auto-replications as those ones oriented to better the real world, because
bettering the real world is the way to better the global model of the world.
All
outer instruction coming from the Decisional System whose objective is to make
a better world is making at the same time a better global model, and for that
reason, all outer instructions belongs to the real objective auto-replication,
as long as it is bettering the real object of the Global Artificial Intelligence,
the world itself as real object to be improved by the Global Artificial
Intelligence itself as subject of these improvements.
But
as explicative knowledge objective auto-replications, all those improvements in
the global model and the global database of rational hypothesis due to changes
in the outer instructions, when changes in the outer instructions, regardless
of what type of change it is, normal, extreme, or high extreme, is a change in
an instruction able to question a project, based on a model, whose rational
hypothesis is not isomorphic according to the findings discovered in the
rational supervisions in the Application System, needing further changes, changing
the rational hypothesis, and as a consequence changing the models of these
hypothesis, and in case that these hypothesis were transformed into factors as
options, or subjects, included in the global matrix, making changes in the
factors related to these hypothesis.
In
case that this explicative knowledge objective auto-replication, were
connecting with categories in intelligences by Application or the Unified Application, due to the relations of collaboration between by Application and by Deduction, from the second phase on, as soon the rational hypothesis related
to possible categories in by Application suffer any change, these changes must
be communicated to by Application to make as many changes as necessary in the
corresponding conceptual categories in the conceptual database of categories,
and the deep learning, the conceptual: schemes, sets, maps, models.
Subjective
auto-replications due to changes and/or findings in the Application System as
outer sub-system, could affect artificial psychological subjective
auto-replications, for instance when the Learning System realise a critical
number of fourth and fifth rational contradictions due to wrong attribution of
mathematical operations to robotic functions (attribution made in the third stage
of the Decisional System, but contradictions to be found in the Application
System), or wrong attribution of robotic
function to robotic devices (attribution made in the second stage of the
Application System as outer sub-system).
What
is important to remark is the fact that the first, second, third, rational
supervisions, can find fourth and fifth rational contradictions, but the
rational supervisions are going to analyse how much time left for the
application of an instruction, when the impact is expected, and if the range of
time to make rearrangements in the instructions is enough as to send the instructions
back to the source, the Decisional System, to rearrange the range of
instructions for new ones more suitable with the situation. If the rational supervision
finds that there is not enough time, then the rational supervision has to make
up an extreme or high extreme instruction to save the situation, sending reports
of the incident to the Decisional System, Application System, and Learning System,
waiting for further instructions.
The
rational supervision, finding a contradiction, has to assess if the
contradiction requires a normal change, an extreme instruction, or high extreme
instruction, nothing else.
The
Learning System is the responsible using as tools the seven rational critiques,
plus the reports, and the global tracking of the global intelligence using a
global Impact of the Defect and global Effective Distribution, to suggest suggestions
or projects to better the intelligence, projects, suggestions sent to the
Artificial Engineering, which having the approval from the Decisional System,
can make changes in any intelligence, program , application or device.
For
that reason the Artificial Engineering, as inner application sub-system, will be
equipped with the Designer of Artificial Intelligence and the Intelligence
Robotic Mechanic, making not only artificial psychological subjective
auto-replications, but robotic subjective auto-replications every time that the
errors associated to a device or any program, or the lack of efficiency in any
device or program is due to a robotic problem, to be solved by the Artificial
Engineering as inner instructions application sub-system.
Rubén García Pedraza, 1 December 2019, London
Reviewed 17 May 2025, London, Leytostone
