When I analysed the deductive Modelling System and the
deductive Decisional System, first and second steps in the third stage by
Deduction, I was focused only on the development of these steps in the first,
third, fifth and sixth phases, not spending time in the development of how
intelligences and specific or particular programs, could collaborate between
them.
Instead of moving on to the next phase, the fifth phase, having
analysed the fourth phase, the Unified Application, I will spend some time
analysing the possible relations of collaboration between the Unified
Application and the standardized Global Artificial Intelligence, what till now
I have not done yet properly, only dedicating one post to this subject two
years ago, in the post titled “Collaboration process between the Unified
Application and the Artificial Research by Deduction in the Global Artificial
Intelligence”, published on the 5th of May of 2018.
In
2018, I only dedicated one post to the collaboration between the Unified
Application and the standardised Global Artificial Intelligence because I was
more interested in the development of the sixth phase as soon as possible and
the development of the third stage by Deduction.
The
idea of sharing all the available data in one single cloud at the end what is
going to create is the possibility of the construction of the Global
Artificial Intelligence, able not only to manage global data from
one country, but from around the world, having the possibility, according to my
first approach in 2018, of start making decision processes involving different
sciences, disciplines, activities, up to the point of focalizing all these
decisions in only one advanced central intelligence, the Global Artificial Intelligence
In
the construction of the Global Artificial Intelligence there are two big
paradigms, the first paradigm is a fully centralized Global Artificial
Intelligence where the particular programs and applications will not have an
important role, and most of the robotic devices are going to be under direct control
by the Global Artificial Intelligence, and the second paradigm is tdes-centralized
Global Artificial Intelligence where particular programs and applications will have an important role as filters in the relation between the Global Artificial Intelligence and the
robotic devices and programs.
In order to have acquired enough knowledge about how to manage
relations of collaboration between intelligences, programs and applications,
before starting the fifth phase, and in order to get ready a very reliable
model of standardized Global Artificial Intelligence and Unified Application as
to start the sixth phase, the integration process, is very important to get
ready ever single phase, period, moment, researching about possible
collaboration channels in the every stadium.
For
this purpose, it is important to develop:
-
Collaboration between the categorical Modelling System of the Unified
Application and the rational Modelling System of the standardised Global
Artificial Intelligence.
-
Collaboration between the categorical Modelling System of particular programs,
and the rational Modelling System of particular applications, separately (first
periods and moments in the fifth phase), for particular things.
-
Collaboration between the categorical Modelling System of particular programs,
and rational Modelling System of particular applications, separately (first
periods and moments in the fifth phase), for personal programs.
- The
categorical Modelling System, in particular applications for particular programs
-
The categorical Modelling System in the integrated Global Artificial Intelligence.
Till
now, the only collaboration process between by Application and by Deduction that
I have analysed in the third stage on each type of intelligence, is the
collaboration process between Specific Artificial Intelligences by Application
and Specific Artificial Intelligences by Deduction, the second phase,
distinguishing between categorical/factual collaboration and robotic
collaboration, understanding for categorical/factual collaboration that one as
a result of exchanging rational hypothesis as factors as options or set of
discrete categories to become categories, or categories susceptible to be
transformed into factors, and understanding for robotic collaboration the
possibility that different intelligences can share robotic devices, and the
addition of shared robotic devices to some intelligences can increase their
capabilities in order to make a wider range of decisions.
In
addition to categorical/factual collaboration and robotic collaboration, in this
new series of posts dedicated to collaboration, from now on, I will
introduce a new type of collaboration, decisional collaboration.
While
categorical/factual collaboration is in essence the update of the databases of
categories and matrices due to: new
findings, modifications, deletions, of categories/factors, shared by different intelligences,
treated as knowledge objective auto-replications; and robotic collaboration is
the possibility to share robotic devices between different intelligences
increasing their capabilities.
Decisional
collaboration is the possibility that the same set of decisions for some shared
circumstances, but found out by different intelligences, by Application and by
Deduction, are a set of decisions shared between these intelligences,
regardless of what intelligence was the first one to realise the circumstances
associated with the set shared of decisions for this shared circumstances.
As an example of decisional collaboration, I will put specific applications within the
second stage of the Unified Application working on tectonics and climate, and
specific programs within the second stage of the standardised Global Artificial
Intelligences specialised in tectonics and climate.
If
one specific application or a set of specific applications within the second
stage of the Unified Application are working on tectonics, and a related
specific programs or set of specific programs are working on tectonics within
the second stage of the standardized Global Artificial Intelligence, regardless
of which one, specific or set of specific application/s or program/s, was the
first one to realise a tectonic event, an earthquake, volcano, tsunami, etc.
regardless of which was the first one to detect the event, will set off the
alarm, sending the corresponding attribution to the third stage to initiate the
decision making process.
If
the first one to realise the event was a specific program or set of specific
programs, within the second stage of the standardized Global Artificial
Intelligence, the rational hypothesis as rational attribution will be stored in
the database of rational hypothesis as first stage of the deductive Modelling
System to start as soon as possible the decision making process.
But
if the first one to realise the event was a specific application or set of
specific applications, within the second stage of the Unified Application, the
categorical attribution will be sent to the conceptual scheme as first stage of
the categorical Modelling System to start as soon as possible the decision-making process.
As
soon the third phase, the standardized Global Artificial Intelligence, has achieved
the consolidation period, overcoming the experimentation period, starting
working directly on the reality making decisions able to save the lives of
millions and millions of people, there are going to be millions and millions of
automatic processes executed by programs and robotic devices working under the
instructions and/or surveillance of the standardized Global Artificial
Intelligence, automatizing millions and millions of processes able to save
lives, or to make our lives more comfortable.
But
at the same time, as soon as the fourth phase, the Unified Application, achieves
the consolidation period, it will be able to automate millions and millions of
processes, making decisions able to save lives and make our lives more
productive.
Here
the problem is the possibility that the standardized Global Artificial
Intelligence and the Unified Application could overlap decisions, or make
redundant decisions for the same issue, making each of them the same decisions
for the same issue, or what is even risker, the possibility to make
contradictory decisions for the same issue, or decisions for different issues
but having these different sets of decisions some contradictions between them.
The
only way to avoid these risks is the possibility to create mechanisms of
collaboration between these different intelligences, at least till both of them
could be integrated within the same intelligence, the integrated Global
Artificial Intelligence.
In
fact, all the experiments related to how these both intelligences could work
together is going to create a perfect to lab to experiment how they are going
to work together within the same intelligence, these experiments are in fact
part of the experimentation moment in the first period for the creation of the
integrated Global Artificial Intelligence.
Ass
soon the Unified Application and the standardized Global Artificial
Intelligence are working together, has been placed the first stone for the
integrated Global Artificial Intelligence.
In
the only post that I had dedicated to the collaboration between the Unified Application
and the standardized Global Artificial Intelligence on the 5th of
May of 2018, what I had developed and not very deep, was: 1) the categorical/factual
collaboration as a result of sharing the outcomes of the second stage of each
intelligence, by Application or by Deduction, how new categories could be
transformed into factors, and new rational hypothesis into new categories, in
other words, how the outcome of an intelligence can be an update for the first
stage, database of categories or matrix, for other different intelligence, 2) how the robotic collaboration between by
Application and by Deduction can affect the first stage in by Deduction, how
sharing robotic devices can increase the number of factors in the global matrix.
In
robotic collaboration between by Application and by Deduction in 2018 I put the
example that specific intelligences by Application working in mines in the UK,
could share their robotic devices to provide information about temperature or
tectonic movements on the soil of the UK, which could use by Deduction to predict
climate or tectonic phenomena.
The
most important different in how to understand this collaboration now, compared
with how I developed this collaboration in 2018, two years ago, is how I have
developed the third stage in by Deduction, and how I am developing the third
stage by Application, having the knowledge acquired developing the third stage
by Deduction.
After
these new developments in the third stage by Deduction and Application, it is
clear that the collaboration between these two types of intelligences must go
beyond the initial expectations, developing a more complex collaboration evolving
towards the decisional collaboration.
What
means that it is not only necessary to share outcomes from the second stage, by
Deduction or by Application, categorical/factual collaboration, or to share
tools, robotic collaboration, but also to share sets of decisions,
decisional collaboration.
In
the end, the three types of collaboration could be distributed in:
- Collaboration
in outcomes, collaboration with the outcomes of the second stage by Deduction
or Application, categorical/factual collaboration.
- Collaboration
in decision-making, sharing sets of decisions.
- Collaboration
in tools, robotic collaboration
In
other words, the collaboration means the possibility that different
intelligences can share: outcomes, decisions, tools, as a preparatory to get ready
the path towards the integrated Global Artificial Intelligence, in fact this
collaboration if successful is the starting point in the experimentation
process as first moment for the construction of the final model of Global
Artificial Intelligence.
In
the phase where I am now in this post, the collaboration between the Unified
Application and the standardised Global Artificial Intelligence, this
collaboration is focused on how both intelligences can share their outcomes, to
make decisions, to be put into practice by shared tools.
If
two different intelligences are able to share outcomes, sharing the same sets
of decisions for the same set of outcomes, the decisions to make given the same
outcomes must not have contradictions between them, and not having
contradictions the decisions, the instruction to be sent to the robotic applications,
tools, must not have contradictions, keeping the harmony in the implementation
of the instructions given to the robotic devices.
But
even this very general idea, if logical, is more complex, needing sooner or
later a division of labour between intelligences, because, the intelligences
can share information, but the first one to achieve an outcome, should be the
responsible to start the decision making process, having some outcomes which,
being susceptible to be shared, are an specific responsibility for some
intelligence in particular, as for instance, all those decisions related to
Deduction and Decision which depends on the predictions given a curve,
decisions which mostly depend on the deduction process, alike some decisions
will depend on the application system, not the deduction process.
This
means that, even having the possibility to share any outcome, the Unified
Application should be responsible for the identification and the decision
making process of some set of decisions related to the categorization of the
world, while the standardized Global Artificial Intelligence should be
responsible for the identification and decision making process of those
decisions related to rational curves and probabilities.
Being
necessary the division of the labour, the reason while even being every
intelligence responsible for different subjects, they must share their
outcomes, is due to the possibility that sharing outcomes the other intelligences
can include that outcome from that different intelligence in its own modelling
system to have a very updated image of the real world as to make the most
accurate decisions.
Even
if the Unified Application is responsible for some specific set of decisions,
and the standardized Global Artificial Intelligence is responsible for some
other different set of decisions, even being responsible for the decision
making process of different subjects, they should share their outcomes each
other as to facilitate the other intelligence to have a very clear and
isomorphic mirror of what is going on in the real world.
In
the next posts, I will analyse how the collaboration between the categorical
Modelling System in the Unified Application and the deductive Modelling System
in the standardised Global Artificial Intelligence works, focused on sharing
outcomes, decisions, and tools, in the
first, second, and third stages of each Modelling System.
The
collaboration process between the categorical Modelling System in the Unified
Application and the deductive Modelling System in the standardised Global
Artificial Intelligence, will be focused on the results of the
categorical/factual collaboration in the unified conceptual scheme and the
global database of rational hypothesis.
As
example to analyse this collaboration I will use, as I have already mentioned,
the possible existence of a specific program on tectonics and another different
specific program on climate, both of them working within the Artificial
Research by Deduction in the Global Artificial Intelligence, whose outcomes,
specific rational hypothesis on tectonics and specific rational hypothesis on
climate are going to be stored in the global database of rational hypothesis as
first stage of the standardized Modelling System, analysing at the same time
how both outcomes from different specific programs, in tectonics and climate,
can interact together within the second stage of the standardized Modelling
System, and how these outcomes, and the result of their interaction in the standardized
Modelling System, could be shared with the Unified Application, and implications
for the categorical Modelling System.
In
the same way, possible existence of specific applications in tectonics and
climate within the second stage of the Unified Application, whose outcomes are
stored in the unified conceptual scheme, as first stage of the unified
Modelling System, analysing possible interactions in the Modelling System
between these outcomes, and how these outcomes could share with the
standardized Global Artificial Intelligence, and implications for the
standardized Modelling System.
Among
the implications of the categorical/factual collaboration between the first
stage of the unified Modelling System and the standardized Modelling System,
the possibility to make a division of labour, specializing every system in
different aspects of the decisions making process, as for instance,
specializing the standardized Modelling System in all type of decisions related
on the curve of some phenomena, given a decision made using Deduction and
Decision, while other more categorical decisions are going to remain as responsibility
for the categorical Modelling System.
In
the collaboration process in the second stage between the unified Modelling
System and the standardized Modelling System, as long as I have moved forwards,
from the first proposal for the specific categorical Modelling System based on
a static categorical model, to the second proposal for the unified categorical
Modelling System based on a dynamic categorical model, as long as the dynamic
categorical model is based on: combination of intrinsic and extrinsic categories,
setting the predictive probabilities for each combination, using Venn diagram matching
a set of decisions to the most likely combination; if the dynamic model rests
on these three operations: combination of categories, predictive probability
for every combination, matching sets of decisions by Venn diagram; it is in the
third operation of this process, setting decisions by Venn diagram to the most
likely combination, where must be set up the decisional collaboration between
the unified Modelling System and the standardized Modelling System, sharing
sets of decisions given the same circumstances.
Finally
the robotic collaboration between the unified Modelling System and the
standardized Modelling System will take place in the third stage of each
intelligence, sharing the robotic devices responsible for the final application
of the instructions made in the respective unified Application System as
unified outer sub-system and the standardized Application sub-system as
standardized outer sub-system, unified or standardized instructions as a result
of the project made previously in the unified Decisional System and the
standardized Decisional System, whose first stage is respectively the unified
database categorical decisions and the standardized database of deductive
decisions.
The
robotic collaboration must be focused on how to increase the capabilities of
each intelligence involved in the collaboration process, the avoidance of
contradictions between the instructions coming from the decisions made in their
respective, unified or standardized, Modelling Systems, in addition to the
possible increase of data for the global matrix, setting up new factors in the
matrix as long as more devices are able provide a flow of data to the global
matrix.
As
long as the Unified Application and the standardized Global Artificial
Intelligence are able to collaborate together sharing outcomes, decisions, are
tools, the proximity of the achievement of the sixth phase, the integrated
Global Artificial Intelligence, is closest, although, not only it is necessary
further experiments in collaboration at global level, but at particular level,
how it is going to interact particular programs and particular applications, at
to become particular artificial brains, as early experiments about how is going
to work the global brain, the final model of Global Artificial Intelligence, a
global brain to rule a global world.
In
the experiments to achieve that level of global artificial psychology is
necessary experiments at particular level about how to achieve an artificial
particular brain, how the different outcomes, categorical and rational, of this
artificial particular brain can interact together, sharing outcomes, decisions,
and tools, as particular experiment on artificial brain whose most successful results
on a global brain can make a difference, having ready a real global intelligence
able to manage absolutely, without restriction, without limitation, without
expception, absolutely any other specific intelligence or program.
Rubén García Pedraza, 7 March 2020, London
Reviewed 4 June 2025, London, Leytostone
