Trans-AI = Superintelligence = Large World/Reality Models + AI/ML/DL/LL models
"Nobody can forecast the future of human world. It is a riddle wrapped in an enigma inside a mystery: but there is a key. That key is man-machine superintelligence. And whoever believes that humanity will do business as usual lost in his fiction reality made of fictional entities".
There is artificial intelligence and Artificial Intelligence, as Fake AI (FAI) vs. Real AI (RAI).
One is imitating, replicating, modeling or simulating human intelligence to effectively substitute it, which is a Fake and False AI.
The other one is imitating, replicating. modeling or simulating reality to effectively complete human intelligence, which is a REAL and TRUE AI.
We advance the Iron Law of Intelligence (ILI/AA) evidenced by all intellectual activities and meaningful human practice:
"World/Reality Modeling/Simulating defines Intelligence and Learning and Inference and Interaction, and vice versa"
No Reality Modeling, No Real Intelligence, and vice versa…
Real intelligence, human intelligence or machine intelligence or man-machine hyperintelligence, consists in its power to effectively interact with the world, as a dynamic causal world model, to be INTERACTIVE as an AGENT INTELLECT (intellectus agens; active intelligence, active reason, or productive intellect)...
The reason for positing a single Agent Intellect is that all (intelligent) entities possess or have access to a fixed and stable set of world's categories, a unified world knowledge of reality (the universe). The only way that all rational agents could possess the same correct knowledge is if they all had access to some central knowledge store, as terminals might have access to a mainframe computer, or task-specific ML models to the cloud AI platforms, or the Internet of Everything to the Future AI Internet.
One of the consequences of the ILI/AA is that the complexity, scope and scale, accuracy and precision, of reality modeling determines the complexity, scope and scale, accuracy and precision, of intelligence, human intelligence or machine intelligence or man-machine hyperintelligence,
This rule refers to all AI, including gen AI, foundation models, LLMs and ChatGPT, to be transformed to Multimodal Large World or Reality Models, following the ILI/AA.
The Rise of Superintelligence
Many believe that a superintelligence is the topic of far future, while missing to see that its special examples are making all the weather in artificial intelligence research, development and technological deployment, from AlphaGo to GPT-x. Such task-specific superhuman AI systems make the short history of explosive growth of machine intelligence and learning, as pictured below.
So, the things with the greatest ever idea in the history of human thought are becoming very very real.
The only difference with all the narrow superhuman AI/ML models, they are lacking real intelligence and learning due to missing a model of all reality, the total sum of all realities or possible worlds (man-machine universal ontology which to automatically categorize, analyze and classify the things in the world, tagging, labeling, or annotating the data to the criteria of the total world model), finding objective patterns (causal links, similarities and differences) in the data to give explanations, discover regularities, make all possible inferences and conclusions and effective interactions.
It is hardly could be replaced with statistical language models or ML training data examples, supervised or unsupervised, however large the training datasets could be.
In the post, we are following up our original studies on Artificial Superintelligence, extending for 25 years, since the 90's:
one of the first books on Artificial Superintelligence (1999)
the book on "Reality, Universal Ontology and Knowledge Systems: towards the Intelligent World" (2008)
the European AI Alliance research papers: "Artificial Superintelligence as the next big thing " (see the Supplement)
Real ASI vs. Human ASI
First of all, some critical assumptions for all further argumentation and inferences.
One should not confuse a realistic and scientific model of superintelligence relying on a comprehensive and consistent model of reality (universal machine ontology) with a non-realistic and non-scientific model of superintelligence relying on the math-statistical modelling of human intelligence.
Again, artificial intelligence or machine intelligence and learning or artificial neural networks or large language models have nothing to do with a computational modeling or simulating of the human brain or intelligence, but an interplay of mathematical techniques, statistical algorithms, probability theory and numerical manipulations
Third, AI has no other sense but to be a superintelligence, a reality-based hyper-intelligence completing human intelligence, designed, developed, and deployed as a real superintelligence system (RSS), a globally distributed man-machine hyperintelligence network.
Real ASI overrules a human-replicating AI in any forms and degrees, as non-realistic and non-scientific misconceptions, be it narrow AI/ML/DL/ANNs models, as large language systems, artificial general intelligence (AGI) or human-like human-level AI, or artificial superintelligence, an autonomous, self-aware AI that surpasses human intelligence.
An RSS solution has a number of core characteristics and technologies. Its key feature is scientific knowledge structured and organized by machine ontology programmed as the world model learning, inference and interaction engine.
To build hyperintelligent machines, we need to teach them the computing world ontology or how to interact with the world, modelled as a causal world hypergraph network encoding all the necessary information of real-world and digital networks such as natural networks, climate networks, biological networks, brain networks, technological networks, computer networks, social networks or virtual networks.
The RSS solutions could be used in almost any field, with the ability to process real-world data and to innovate and solve problems across fields like philosophy, mathematics, science, technology, engineering, medicine, the arts, etc.
Humanity is in need of RSS for several reasons:
Superintelligence = Real and True AI = All Reality Model [Machine Ontology, Intelligence and Learning] + Narrow AI/ML/DL/LL Models
AI as ML, DL or ANNs, LLMs, AGI or ASI is all about mathematical techniques and statistical algorithms, probability theory and computational manipulation.
It is a mystification or bad science to anthropomorphize it all as that which “enables computers and machines to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind”.
Or, as human-like machines which would feature highly advanced reasoning, decision-making, and problem-solving capabilities far beyond the creative or logical capabilities of any human being.
Making sense of the world, inferring cause-and-effect relationships between variables, understanding and analyzing the causal relationships between events, or learning to reason about causality, causation or interaction, is a hallmark of intelligence systems, natural or artificial.
If your AI/ML/DL/LLM is unable to reason about the world or the environment around you, it is absolutely unintelligent.
If your software applications, as LLMs or GPT-x or ChatGPT, are unable to solve causal reasoning problems , they are absolutely unintelligent.
LLMs are trained on the internet datasets to extrapolate or interpolate, "predict" sequences of words generating human-like text/code/image/audio on demand. LLMs are nonintelligent due to the very design, wanting an encoded world learning, inference and interaction model, or the power of making sense of the world of complex cause-effect relationships.
Real Intelligent AI is about reality and truths, models and facts, of reality and by reality, with the real intelligence system architecture:
Real AI Technology (RAIT) = RSS = the world or reality (the real world, the environments, the internet, virtual reality, etc.) + reality modeling and simulation and interaction engine [perception (sensors, the internet of things, robotics) + knowing/conception/classification + inference/reasoning/decision making (GOFAI) + learning (ML&DL&ANNs) + actuation (actuators, robotics)] + the environment (the real world, the internet, virtual reality, etc.)
AI World Model [Ontology]
AI must be intellectualized by its onto-semantic reification with machine ontology, semantics and science, grounding its data models and algorithms to the world or reality, its entities and interactions and causal relationships.
Again, it should not be a reification fallacy (concretism, hypostatization, or the fallacy of misplaced concreteness), a pathetic anthropomorphic fallacy, human characteristics, especially intelligence, thoughts or feelings are attributed to some abstractions, mathematical models or statistical algorithms treated as if it were a concrete reality or physical entity.
Or, to become real and true, genuine and actual, it must be driven by some world model of its environment, tasks and jobs or application domains, from object/face/speech/text recognition, communication, content generation, recommendations, predictions and decisions to NLG/NLU.
Without its ontological data-environment semantic model, self-driving cars are unable to "continuously identify objects in the environment around the car, predict how they will change or move, and guide the car around the objects as well as toward the driver's destination".
So, Real and True AI is a Reality-centric AI, the world-driven machine intelligence and learning.
As AI is emerging as a cardinal feature of the world, the category of ontological superintelligence (OSI) is becoming one of the highest genera or kinds of entities, interrelating the topmost world's variables:
The World as a whole (W) as all reality (R), the whole Universe, all Existence, Everything that exists, the sum total of all possible worlds or realities, physical, mental or digital, with all lawful possibilities and shapes of space and time, or the universal class of the sets of all realities, the totality of possible entities and interactions
Entity (E), Thing (T), Object (O), or Being (B) the universal class of the sets of all entities or things or objects or beings
Substance, Matter, Material, Mind, the universal class of the set of all substances
State, Quality or Quantity (Q), Property or Condition, the universal class of the sets of all states, qualities and quantities, properties or conditions
Change (C) or Event or Process (P), the universal class of the sets of all changes, events and processes
Relationship (R), Interaction (I) or Causation (C), the universal class of the sets of all interactions and causal interrelationships
Data (D), Information (I), Knowledge (K), the universal class of the sets of all representations:
Ontological Superintelligence or RSS (RSS), the universal class of the sets of intelligent beings (as humans, intelligent machines or artificial intelligence (AI)).
The Formula of Real Superintelligence
A Superintelligence is mapping/modelling/simulating/manipulating/interacting with Reality/Input, as World Representations (Stimuli, Signs, Symbols or DATA (D)), to generate Intelligent Output, Predictions and Explanations, Meaning and Information, Interaction, as Man-Machine Hyperintelligent Hyper-Automation Technology.
OSI [HI; AI]: W (E, S, Q, P, C) > D (W) = World Data, Entity Data, Substance Data, State Data, Change Data, Interaction Data or Relationship Data (Laws and Rules, Regularities and Patterns, Structures and Functions, as Datasets and Relational Database, Statistical Algorithms as Regression Algorithms and Neural Networks, AI models or ML Inferences, Generative AI or LLMs, etc.)
Or, reality is representing as a universal undirected hypergraph learning and inference (W, W x W), with virtually an unlimited order, the number o vertices, and size, the number of edges, where hyperedges or hyperlinks interrelate, interconnect, associate, correlate or interact an arbitrary number of nodes.
领英推荐
R = <W, W x W>
In such global causal networks of entity dots, vertices, nodes, points, or elements interconnected by lines, links, or hyperedges, machine ontology quantifies the encoded information of each piece of reality, be it QM, ANNs, biological, social or musical domains .
As an example, [researchers using tools from information theory, statistics and physics analyzed 337 musical compositions by German composer Johann Sebastian Bach. By representing his scores as simple networks of dots, called nodes, connected by lines, called edges, scientists quantified the information each piece of music conveyed] .
The Fundamentality of RSS
The RSS is a Reality-driven or World-grounded AI or Real and True AI, which simulates and models the reality itself to effectively navigate, adjust, adapt or interact with the world, its domains and environments, systems and structures, including mentality and virtuality.
Its World Model Engine as Ontological Categorization, Knowing and Learning, Inference and Interaction Framework is reified or instantiated by
human intelligence and practice
real life and culture
economics and politics
science and engineering
mathematics and statistics
the arts and humanities
physical technology and digital technology
AI, machine intelligence and learning,
intelligent entities and robotic agents,
statistical learning algorithms,
specialist/narrow AI,
large language model-based generative artificial intelligence technologies,
generalist AI, AGI,
hyperintelligence and superintelligence.
The Real AI embraces the OECD's conception of AI : "An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment".
Last, not least, real/ontological superintelligence models have no need for any superintelligence human alignment, like reinforcement learning from human feedback (RLHF), relying on human supervision.
Resources
We believe superintelligence—AI vastly smarter than humans—could be developed within the next ten years. However, we still do not know how to reliably steer and control superhuman AI systems. Solving this problem is essential for ensuring that even the most advanced AI systems in the future remain safe and beneficial to humanity.?
SUPPLEMENT: Artificial Superintelligence as the next big thing
The next really big thing is not some sample of exponential technologies, as different experts like to recall: ML/DL, quantum computer, additive manufacturing, augmented and virtual reality (AR, VR), digital biology and biotech, data science, smart medical tech, nanotech, robotics, autonomous vehicles, etc…
Exponential Technology | Deloitte Insights
The viable and sustainable solutions of the world’s most complex problems can be found at the intersection of exponential technologies.
The next big thing?is the fusion of exponential technologies, as the top techno-human convergence of human-cyber-physical systems, titled as Artificial Superintelligence (ASI) as succeeding AGI.
Kiryl Persianov's answer to Is AGI possible?
ASI is now emerging as the universally distributed hybrid human-digital global intelligence, driven by digital ontology, global data platform, master algorithms, AutoML/DL platforms, 5G, to be implemented as AI Internet.
ASI?embraces Human Individual and Collective intelligence (CI), a group intelligence that emerges from the collaboration, collective efforts, and competition of human minds, used in sociobiology, political science, crowdsourcing applications, social media, etc.
Human collective intelligence is an emergent property from the synergies among: 1) data-information-knowledge; 2) software-hardware; and 3) experts (those with new insights as well as recognized authorities) learning from feedback loops of reinforcement learning.?Collective intelligence - Wikipedia
ASI also covers the "global brain" as the emerging intelligent network formed by all people on this planet, together with the computers and communication links that connect them together. An immensely complex, self-organizing and decentralized system, it is to process data-information-knowledge, make decisions, solve problems, learn new connections, discover new ideas, etc, playing the role of a collective nervous system for the whole of humanity”.?The Global Brain FAQ
The Global Brain Institute/The Global Brain as the distributed intelligence emerging from the Internet
ASI is thus emerging as the integration/synthesis/synergy/fusion/combination of human collective intelligence and exponential technologies:
specific artificial intelligence, machine learning and deep learning systems,
advanced robotics, cognitive robots and drones,
the Internet, internet of things,
5G, mobile internet, smart phones,
virtual and augmented reality,
additive manufacturing and 3D printing,
blockchain technology,
autonomous vehicles,
nanotechnology,
alternative energy systems,
biotechnology, digital medicine, etc.
Technology Trends - Exponential Technology Trends Defining 2019
Due to AI, a rational man is becoming a superintelligent transhuman being:
a homo sapiens + smartphone + Internet/Web/Google + World Data/Information/Knowledge + AI cloud + the IoT +…
Resources
Real AI Manifesto: Artificial Global Intelligence (AGI)
"Whoever Creates Real Artificial Intelligence Will Rule the World"
Universal computing ontology as applied to human minds and general AI:
Fascinating insights on artificial intelligence and machine learning evolution! ??