A Global AI Infrastructure: RAI vs. BRI as the Most Valuable Project on the Earth
Real AI [General Machine Intelligence and Learning] as an Effective and Efficient and Truly Intelligent AI is one of the most challenging, valuable and expensive scientific and technological, social and industrial projects, including
The RAI technology is an enabling, general-purpose technology which could bring ubiquitous disruptive changes in the human society, its social order, economy, industry, politics, communities, and all the ways of living.
Of all prospective emerging technologies, social technology, educational technology, information technology, quantum technology, nanotechnology, biotechnology, neurotechnology, robotics and cognitive technology, the Real AI technology is the next and last big thing, embracing and converging all the digital and emerging technologies.
Among other social and economic, scientific and technological, political and cultural sustainable disruptions, the RAI Technology is disrupting the Non-Intelligent Forms of Industrialization 1, 2, 3, 4, which have led to many of the world’s problems and global risks and threats, as current environmental problems, like as climate change, lethal levels of air pollution, the depletion of fishing stocks, toxins in rivers and soils, overflowing levels of waste on land and in the ocean, loss of biodiversity, deforestation and natural disasters.
Below I outline some basic technical points of RAI: How could the source code of it look like? What is the history of real intelligence technology? What are the key components of RAI?
Coding Man-Machine Superintelligence
Creating a Real AI/AGI is about creating a computing machine that has encoded the AI World Model Engine with the power to deduce/infer/learn domain models of the world itself from all the real world data/information it gathers from the digital, social or natural environments (via its IoTs/sensors).
Being able to perform all sorts of tasks, it should have the capability to continuously learn and gain huge knowledge, across all domains and activities. Thus, such a real and true intelligence wouldn't contain millions or billions of lines of code. Instead, it'll be built with a very basic lines of code, that is recursive and infinitely extendable. The RAI/AGI will then learn on its own - with no human intervention or programming.
We would need code for:
To compare, here’s a diagram of the biggest codebases in history, as measured by lines of code: Google has by far the largest codebase of all, and all 2 billion lines of code fits into a single code repository
To get some basic ideas, go to the external source:
A Long Intellectual History of Real Intelligence Science and Technology
For its long conception 2300+ years and short development lifetime of 70+ years, the idea of intelligence has passed many phases and stages to reach its true status of Man-Machine Superintelligence:
Aristotle's Analytics/Metaphysics... >
Mathematics & Logic >
Science and Engineering >
Computing and IT >
Cybernetics >
Neural Networks >
NLP >
Formal Logical AI >
Intuitive Physics AI >
Experts Systems >
Statistical Learning >
Data Analytics > Data Mining > Predictive Analytics >
Machine Learning > Deep Learning > Multimodal Learning >
ANI > AGI > ASI >
Causal Machine Intelligence and Learning >
Quantum Computing > Quantum Information Science > Physical Quantum Computers > Quantum AI >
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Real AI > Transdisciplinary AI = Trans-AI = Man-Machine Superintelligence
Real AI is emerging as [Human-Machine] Hybrid Intelligence, a Transdisciplinary AI (Trans-AI) or Meta-AI or the Man-Machine Supermind or Hyperintelligence, integrating symbolic AI and Neural ML, be it Artificial Narrow Intelligence, Artificial General Intelligence, Artificial Superintelligence, with Collective Human Intelligence.
What are the essential elements of Real AI?
Reality/Causality/Mentality/Environment/Simulation/Modeling/Perception-Action-Interaction Mechanisms/Robotics/Sensors/Actuators
Data/Signals/Symbols/Information/Knowledge/Science & Engineering/Arts/Common Knowledge
Intelligence/Understanding/Categorization/Classification/Master Algorithm/Learning Algorithms/Machine learning/Deep learning/neural networks/DNNs
NLU/NLP/NLG
Programming/Coding/AI Software
Hardware/AI Processors/AI Platforms/AI applications
It is the architecture of Real AI, as Causal Machine Intelligence and Learning, requesting an encyclopedic knowledge in a wide variety of fields of philosophy, mathematics, science, engineering and the humanities.
All in all, RAI researchers should have a good understanding of Reality, Data, Information, Knowledge, and Intelligence.
The concept of RAI leads to the new human techno-philosophy that “people should embrace all knowledge and develop their capacities as fully as possible”, if not to be disrupted by the human-like AI machines.
Sources
Real AI Project Confidential Report: How to Engineer Man-Machine Superintelligence 2025: AI for Everything and Everyone (AI4EE); 179 pages, EIS LTD, EU, Russia, 2021
Content
The World of Reality, Causality and Real AI: Exposing the great unknown unknowns
Transforming a World of Data into a World of Intelligence
WorldNet: World Data Reference System: Global Data Platform
Universal Data Typology: the Standard Data Framework
The World-Data modeling: the Universe of Entity Variables
Global AI & ML disruptive investment projects
USECS, Universal Standard Entity Classification SYSTEM:
The WORLD.Schema, World Entities Global REFERENCE
GLOBAL ENTITY SEARCH SYSTEM: GESS
References
Supplement I: AI/ML/DL/CS/DS Knowledge Base
Supplement II: I-World
Supplement III: International and National AI Strategies