All is Interaction: Trans-Science & Trans-Technology & Trans-AI

All of reality is interaction

All of reality is interaction, it starts from interaction, goes through interaction and restarts from interaction.

In physics, the fundamental interactions or fundamental forces are the interactions that form the basis of all known interactions in nature: gravitational, electromagnetic, strong nuclear, and weak nuclear forces. They appear to be unified by more basic interactions, as a single fundamental meta-physical force or proto force or hyper force.

To discover the fundamental hyper interaction or proto force is a way to a?meta-physical theory of everything?(MTOE),?a universal formal ontology, final theory,?ultimate theory,?or?master theory, a singular, all-encompassing, coherent?framework that explains, predicts and interrelates all aspects of the?world.

It is to cover a physical TOE, a unified field theory, unifying all the fundamental interactions of nature, merging all physical branches:

In the infinite universe, all is interconnected and nothing exists alone, be it elementary particle, stars and galaxies or the universe itself. For any entity to exist, it is to interact with other entity.

One thing can't exist by itself, it is is hyperlinked to all the world, to something specific or everything else.

The first thing was not god or matter or radiation, but Interaction, Proto Force. Through the Interaction all things came into effect.

All exists by interactions and through interactions, or all the universe is an infinite web of interaction networks.

The universe is a universal interaction network with causal links, feedback loops and interactive mechanisms, reinforcing (R) or balancing (B), creating virtuous or vicious cycles or restoring equilibrium or stability.

The world is governed by causal algorithms and transformative mechanisms.

Living bodies are causal machines. Animal brains and minds are interactive causal mechanisms. AI machines are causal machine intelligence and learning.

Reality is the universal network of ontological/causal variables and parameters. All is structured by causality and causation, mechanisms and interactions.

Reality is what we need to know

REALITY is the giant causal networks of systems of entities, governed by fundamental interactions, causal mechanisms, principles, laws and effects.

Its physical, mental, social or digital domains are modelled the interaction graph networks consisting of nodes or vertices or points (causal variables), arrows or edges or lines (causal links), and signs ( S, + or -) that indicate the polarity of the link and feedback loops, circular chains of causes and effects, reinforcing (R) and balancing (B), amplifying changes, creating virtuous or vicious cycles, or balancing loops counteracting changes, restoring equilibrium or stability, interacting (I) with one another, leading to complex phenomena and nonlinear processes:

R = <V, E, S, R, B, I> (1)

The formula just created applies to any interaction or cause and effect, any causal mechanism, and any effect, or any complex systems and phenomena. It is a general formula of real-world, interactive causality.

A close example is multiple neural circuits or biological neural networks interconnecting with one another to form?large scale brain networks or intrinsic brain networks, inspiring the design of artificial neural networks, the workhorse of today's AI/ML/DL.

ANY COMPLEX SYSTEMS, BE IT THE WHOLE UNIVERSE OR QUANTUM SYSTEMS, IS THE CAUSAL NETWORK OF THINGS, THE WEB OF INTERACTIONS.

ANY CONCEPTUAL, SCIENTIFIC, MATHEMATICAL OR COMPUTATIONAL MODELING OF REALITY follows the key types of causal networks analysis,?simple linear models, complex linear models and complex non-linear interactive models.

ANY INTELLIGENCE, BE IT SUPERINTELLIGENCE or HUMANS, ANIMALS or MACHINES, follows the World (natural environment, humans, information processing systems, agents,...) - Complex Systems Interaction Algorithm, as in:

Reality as the universal interaction networks and its realms (Physical or Mental, Social or Digital) - Causal Input (Matter, Energy, Information) - Causal Mechanism/Function/Operation/Algorithm/Transformation - Causal Output (Matter, Energy, Information) - Causal Feedback, with all the transformation and translation, explanation and transparency, inference and prediction, actions and reactions and interactions - Reality (Physical or Mental, Social or Digital).

A close example is a neural network as a predictive analytics method in ML/AI that teaches computers to process data in a way that is inspired by the human brain, while learning and modeling the relationships between input and output data that are nonlinear and complex. ?Artificial neural networks learn continuously by using corrective feedback loops to improve their predictive analytics.

Other example is possible prompts for AI/LLMs/ChatGPT, from a simple linear prompt to the complex causal loop diagrams, with ''the Human-in-the-Loop (HITL)?enabling human verification and corrections to ensure accuracy of data extracted by Document AI processors before it is used in critical business applications, as across Financial Services, Health, Manufacturing, Government and other industries."

In all, ALL REALITY is interaction...to master causal interactions is to master the most complex things in the world, the world's nature and general intelligence, human and machine.

#TransScienceTechnology: transdisciplinary, transformative, and translational science and technology

The universality of interaction enables the consilience and convergency, integrity and synergy of science, technology and engineering, It inspires Trans-Science & Technology (TST) (i.e., Trans-Science, Trans-Technology and their hybridization) thinking and vision, paradigms and models, approaches and practices. TST features its?transformative,?transdisciplinary, and?translational?S & T in terms of thinking, paradigms, models, techniques, methodologies, technologies, engineering, and practices.

Science is generally defined as in:

"the systematic study of the structure and behaviour of the physical and natural world through observation,?experimentation, and the testing of theories against the evidence obtained".

"any system of knowledge that is concerned with the physical world and its phenomena and that entails unbiased observations and systematic experimentation".?

"a pursuit of knowledge covering general truths or the operations of fundamental laws".

Science is commonly divided into different branches based on the subject of study, as in: the physical sciences of the inorganic world of matter and energy and its processes; the life sciences of the organic world of life and its processes; the social sciences of the social world of humans and their behavior; the formal sciences of formal systems, axioms and rules; and applied sciences, which go as technology, as engineering and medicine.

Technology is the application of scientific knowledge to the practical aims of human life or, to the change and manipulation of the human?environment.

Developing transformative, transdisciplinary, and translational science, engineering and technology is inspired by inspired by and surpasses the scope and capacity of existing thinking and practice in transformative research, transdisciplinary science, and translational research.

S & T transformation, transdisciplinarity, and translation drive original and innovative, important and leading-edge models, thinking, areas, paradigms, theories, technologies, engineering, practices, etc.

The complex interactions of philosophy and science, engineering and technology could emerge as , with disruptive, outside-the-box, and ‘beyond’ methods, with TST thinking, TST paradigm, TST R & D, TST engineering, TST practice, TST business, etc.

TST is defined as the systematic study that builds and organizes world's data/information as world's knowledge in the form of causal models, explanations and predictions about the universe, its natural and other phenomena and interactions.

The TST models the interactive world, or the universe of all possible realities, as the universal network of interacting causal systems, at all possible scales and scopes.

It embraces the systems theory's view of a?system?as "a group of interacting or interrelated elements that act according to a set of rules to form a unified whole", marked with its components and connections, elements and wholes, factors and variables, quantities and qualities, states and changes, structure and function(s), pathways and circuits, patterns and regularities, behavior and interconnectivity, boundaries and the environment.

In a complex dynamic system or network of systems, everything is interrelated to everything else. Causal Loop Diagrams (CLDs) are used to conceptually model dynamic systems in a holistic manner, mapping how variables (i.e., factors, issues, processes) interact or influence one another.?The interactions or relationships, not independent elements, drive the outcomes and behaviors which are to model, study, understand.?One cannot understand something, its constitutive parts (instances, factors, actors, processes) in isolation, without knowing its interactions and interrelationships.

TST transcends the systems science and engineering as dealing with any?systems or networks—from simple to complex—in?the universe or nature,?brain and mind,?science?and technology, engineering and?business,?life and environment:

physical systems, chemical systems, biological systems, neural networks, mental systems, social systems, information systems, technological systems, engineering systems, industrial systems, urban systems, world systems, environmental eco/climate systems, or computer networks as the internet.

It could be viewed as a New Tektology, which universalizing and reifying Malinovsky's tektology, and its modern systems' extensions, the general systems theory, systems science, cybernetics, synergetics, chaos theory, systems dynamics, statistics, computer science and technology, or systems engineering. "Tektology/tectology: a new universal science that consisted of unifying all social, biological and physical sciences by considering them as systems of relationships and by seeking the organizational principles that underlie all systems".?Tektology: Universal Organization Science, A. Bogdanov, 1912 - 1922.

Reality or the world or nature has a general, organized character,?with one set of interactive [causal] laws of organization for all objects, all modelled by the TST.

The reality of the complex construct of is proved by the fundamental fact of being the foundation of the most challenging concept in the history of ideas: an Interactive AI (), a real or true artificial intelligence (TRAI), as "the science and engineering of intelligent machines", commonly confused with a human-like, non-interactive AI as "the simulation of human intelligence processes by machines, especially computer systems".

Since "AI is quite possibly the most important – and best – thing our civilization has ever created, certainly on par with electricity and microchips, and probably beyond those".

Such a real AI is constructed as Transdisciplinary Machine Intelligence and Learning, conceptualized as , going beyond and across all the narrow and weak AI models, techniques, algorithms, computer technologies, and applications, from machine learning (ML) to deep neural networks (DNNs), search engines to generative tools and large language models (LLMs), as pictured below:

models allow world's data to be analyzed by causal models and algorithms with all accuracy and efficiency, enabling general or specific problem solving and knowledge discovery in any fields of study or practice: computer science; education; humanities; medicine; agriculture; sciences; engineering; law; business; ecology [Trans-AI: How to Build True AI or Real Machine Intelligence and Learning]

Trans-AI models imply the Human-in-the-loop (HITL) AI that leverages both human and machine intelligence to create real-world machine intelligence and learning models. People are involved in a virtuous circle where they train, tune, and test a particular algorithm but referencing to the world model learning and inference engine. One could train his TransAI model using Reinforcement Learning from Human Feedback (RLHF) while interacting in a conversational way relying on the causal world knowledge framework to avoid subjectivity.

To be is to interact, to interact is to be: all the things in the world interact

The world we live in is multicultural with a corresponding plethora of worldviews and never-ending paradigm wars, often transforming to real wars with huge damages and enormous casualties.

In reality, there is single fundamental and all-underlying paradigm of causality as interaction, which governs all the principles and laws, rules and regularities of nature and society, science and technology.

Interaction via causality and causation, forces, effects, impacts, agencies and influences, fundamental interactions or forces, is the only fundamental and universal interrelationship for networking and relations, interconnections, interlinks, interdependencies, associations, correlations, intercommunication, bonds, ties, unions, interfaces, etc. The concept of interaction could be measured in different ways and methods, indicating the progress in science and technology, For example, in information science it could be ?"the mutual information as the amount of information (reduction in uncertainty) that knowing either variable provides about the other".

To master/learn all major interactions as reciprocal actions or causal interrelationships or mutual dependencies is to master/control the world or the domain of interest.

Interaction is ontologically prior to all and everything, be it thing and entity, quality and quantity, state and event, change and process, time or space, as well as any category or concept, notion or idea.

The first was the Prime Cause, be it God or the Big Bang, to which every chain of causes and interactions must ultimately go back, to the fundamental interactions and beyond.

It is not that the Cause is God, and the Effect is the World, but rather the Cause is Interaction, and the Effect is the World.

Interaction is All and Everything

The study of [non-interactive] causality extends from ancient philosophy to contemporary science and engineering.

Causal learning has its roots in metaphysics since Aristotle's four causes: material (what something is made of), formal (i.e., structural, how something is made, its structure and form), efficient (or moving; necessary for the effect’s existence), and final (i.e., functional, the purpose, an egg is the cause of a chicken).

Following Aristotle, Thomas Aquinas innovated "the first cause argument", which is based around?cause and effect. The?cause is God, the?effect is the world. The idea is that everything that exists has something that caused it, there is nothing in our world that came from nothing. And the first cause is?eternal.

Regardless, we know almost nothing about causality, its essence and nature, agents, kinds, levels, scopes, scales and mechanisms, namely:

• What is a causal world, universe, reality?
• What is a causal entity and relationship,
• What is a causal system and network?
• What is causal brain and mind, intelligence and understanding, learning and cognition, volition and decision-making, behavior and interactions?
• What is causal data, information and knowledge?
• What is causal science and technology?

Some effort to create the science of causality is only confusing things more, like "correlation is not causation" and?the 'ladder of causation' of Association, Intervention and Counterfactuals.

All modern causal paradigms are driven by the long-standing and harmful illusion of linear, one-sided, unilateral causation, as the one-way, asymmetrical relation between a cause and its effect. It is as defined in the Wiki: "Causality, as?causation, or?cause and effect, is influence by which one event, process, state, or object contributes to the production of another event, process, state, or object where the cause is partly responsible for the effect, and the effect is partly dependent on the cause".

In reality, as to the AA Interaction Principle of the Universe, All is Interaction, or

"Everything interacts with everything else: something (A/X) causes something else (B/Y) if and only if the something else (B/Y) causes the something (A/X)".

"In the real world—the world we live in—we always find that there are many causes?x1,?x2,?x3…xn. There are also many causal mechanisms?φ1,?φ2,?φ3…φn. And there are many effects...?The formula applies to any cause, any causal mechanism, and any effect. It is a general formula of causality".?

In probability theory and information theory, the construct of interaction as the mutual dependence between two or more random variables could be measured by the joint probability distribution, P(A,B) or P (X,Y), where X,Y are a pair of random variables with values over the interaction space?X x Y.?In probability theory and statistics, it is formulated as Bayes' theorem,?Bayes' law?or?Bayes' rule, with ontological/physical/objective/frequentist or subjective/evidential/epistemic/logical/inductive probability interpretations: P(A;B) = P(A/B) P(B) = P(B/A) P(A)

and/or the mutual information or the joint entropy H (X,Y), introduced by Shannon in his landmark paper "A Mathematical Theory of Communication":

All in all, the following ontological principles and rules make the basic causal knowledge about the interactive world, studied by TST:

• The World, Reality, Being, Existence, or Universe is the Sum Total of All Interactions
• Causality is an interrelationship where a change in one variable necessarily results in a change in another variable, and vice versa.
• Causality is Interaction and Interaction is Causality
• Causal feedback loops are all the interactions that matter, as the reinforcing causal loops or balancing causal loops of key variables
• To learn interactions is to master the world of all causal variables, for a variable contains as much information about itself as any other variable can provide

Conclusion

All of reality is interaction; interactions create all the substances, states, changes and relationships, all the networks and systems, all the phenomena and processes, forces and emerging properties,?including all the intelligence, natural or artificial.

Interactions are studied by the TST, which is the conceptual foundation of the Trans-AI, as an Interactive Machine Intelligence and Learning.

SUPPLEMENT. Causal Decalogue

1. The world is the whole of?reality, all and everything that was, is and will be, the totality of entities and interrelations.
2. The universe consists of substances (objects), states (qualities and quantities) and changes (actions, events, processes) standing in causal interrelationships.
3. Interaction/Causation is the master principle and prime force of the universe.
4. There are no uncaused things or changes in the world.
5. Interactivity/Causality gives structure or order to everything in the world, from the microworld to the macroworld.
6. Interaction/Causation determines the hierarchical structure of world, its entities, processes and relationships, as well as its data, information and knowledge.
7. Interaction/Causation is reverting, reversing, reacting, and going backwards, creating dynamic backward loops and causal circuits, complex control systems and nonlinear processes.
8. Interaction/Causation flows in bottom-up ways, from micro to macro scales, as causal emergency, and vice versa, in top-down ways, from macro to macro scales, as causal control.
9. The interrelationships of microscales and macroscale are determined by the top-down and bottom-up interactive causation.?
10. Interaction/Causality is the universal interrelationship, which is a symmetric productive and correlative relationship, X causes Y if and only if Y causes X.

Corollaries

The world is the totality?of all entities, structured by nonlinear causation, or interactions.

The world is the global causal net. All is causal networks.

The physical world or universe is the totality?of all matter and energy, space and time; all that is, has been, and will be, all governed by causal?interactions, as fundamental forces, gravitational, electromagnetic, strong and weak.

Causation gives deep structures and ordering to mind, intelligence, learning, inference, cognition. reasoning, understanding, and action, human or machine.

Causal models, rules and relationships are the master models and algorithms for artificial intelligence, machine learning, artificial neural networks and deep learning.

Resources

The CAUSAL DECALOGUE: The 10 Commandments about the world for humans and AI machines

The Ultimate of Reality: Reversible Causality

The centerpiece of the world: real causality/nonlinear causation: interrelationships and interactions: Real/causal AI/ML/DL

What Determines the World: Causality as the Life-or-Death Relationship

AA/AI Rule for Autonomous Machine Intelligence: "There is no True AI without Understanding the Cause and Effect of Interactions within the World"

World Data Ontology: Data Science and Engineering, AI, ML, Deep Learning, Knowledge Graph, and Smart Web Search

https://www.dhirubhai.net/pulse/smart-data-global-platform-investment-artificial-big-abdoullaev/

https://www.dhirubhai.net/pulse/world-data-ontology-science-ai-ml-deep-learning-graph-abdoullaev/

Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science