AI as a digital superintelligence platform: 5D (description, design, development, deployment and distribution worldwide)

  • Azamat Abdoullaev
    The best way to forecast the future is to create it
    61 статья 

    Prologue, AI Supremacy, the Holy Grail of Artificial Intelligence (AI) R&D

    AI is becoming a global scale platform and general purpose technology, succeeding Electricity and Information Technology (IT) as the two most important GPTs so far.

    It has been proven by the G7 Declaration of the International Panel on Artificial Intelligence, including the following members:

    France, United States, United Kingdom, Russia (suspended), Germany, Japan, Italy, and Canada, invited Russia and India.

    Declaration of the International Panel on Artificial Intelligence

    There is Global Partnership on Artificial Intelligence (GPAI) to support the responsible and human-centric development and use of AI.

    Founding members are: Australia, Canada, the European Union, France, Germany, India, Italy, Japan, Korea, Mexico, New Zealand, Singapore, Slovenia, the United Kingdom and the United States.

    The author confirms a real plausibility and possibility of creating AI as a digital superintelligence or machine superintelligence greatly outsmarting and outperforming the human minds and collective intelligence, and thus promising revolutionary technological, scientific, social and economic advances and deep implications for global governance and public policy.

    The first digital superintelligence model was described, designed and developed with a view to deploy and distribute it worldwide as a Global Scale Platform and General Purpose Technology.

    The superintelligent AI model covers a conceptual view of an AI produced by the Expert Group on AI at the OECD.

    The digital superintelligence model embraces a conceptual view of an AI produced by the EU High-Level Expert Group on Artificial Intelligence (AI HLEG). 

    The reality of digital superintelligence has been first recognized by Elon Musk, the founder, CEO, CTO and chief designer of SpaceX; early investor, CEO and product architect of Tesla, Inc.; founder of The Boring Company; co-founder of Neuralink; and co-founder and initial co-chairman of OpenAI.

    "We are rapidly heading towards digital superintelligence that far exceeds any human". "I think it's very obvious." "We have five years. I think digital superintelligence will happen in my lifetime, 100%."

    But our digital superintelligence model discovery refutes any necessity for AI regulations; for the speculative predictions of its existential risks have no scientific evidence, as in:

    “If one company or small group of people manages to develop god-like superintelligence, they could take over the world.”

    “Thus the first ultraintelligent machine is the last invention that man need ever make” I.J. Good, Speculations Concerning the First Ultraintelligent Machine

    Busting AI myths

    As everything highly mysterious, AI has its own myths, as two kinds of errors:

    ·        false positive, a narrow AI of machine learning systems and deep neural networks,

    ·        false negative, superintelligent AI, some condition does not exist when it really is.

    As a result, many philosophers, futurists, and AI researchers have boldly time-guessed that even human-level AI will be developed in the next 20 to 200 years, with the laymen believing it is a never case.

    But Never Say Never.

    Our extreme intellectualism has constantly and stubbornly pursued the same goal of building a supreme intelligence which is processed, stored or communicated across space and time and human minds, like as coded information.

    During more than three decades, socially isolating myself on a Med island, mostly living online, I have made three leapfrogs to reach the sky:

    I. Artificial Superintelligence-1999. It is largely based on a fundamental (causal) theory of everything. Combining the top most categories of reality, the idea of pure intelligence, the major constructs and facts of science and mathematics, the author proposes a theory of powerfully intelligent machines superior to human minds. 

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    II. Superintelligence-2008

    Reality, Universal Ontology and Knowledge Systems: Toward the Intelligent World provides cutting-edge research on reality, its nature and fundamental structure, and how it may be effectively represented both by human minds and intelligent machines. Striving to create a standard world model as a universal formal ontology, it offers a uniformly organized human knowledge of the world. The book instructs how to develop real world intelligent technology with ontological reasoning mechanisms (meta-physical semantic machines) and secure communication interoperability between two species of intelligences, existing human beings and nascent encyclopedic intellectual systems promising the profound revolution in human values and ways of life.

    III. Superintelligence-2020. Now I could state about a final solution of the hardest ever problem human intellects had met in the intellectual history. Let’s look how it looks the discovery of all discoveries, the constructs of all constructs, the invention of all inventions, the intelligence of intelligences.

    Here is our “Announcement"

    As a member of European AI Alliance, EIS Encyclopedic Intelligent Systems has developed the first real model and system architecture of AI as a superintelligent AI or machine superintelligence or universal AI or global AI, i.e., true AI, real AI of general machine learning self-knowing systems and causally deep neural networks, all emerging as ultraintelligent machines.

    <Artificial Superintelligence as the next big thing:>

    What kind of entity is a superintelligence, its architecture, components and elements?

    Real AI includes the following architectural components:

    • Machine World Model (The WORLD.Schema, World Entities Global REFERENCE; Universal Human-Machine Ontology; USECS, Universal Standard Entity Classification SYSTEM);
    • Master Algorithm (for symbolic and sub-symbolic machine learning algorithms, as deductive and inductive reasoning, connectionism, evolutionary computation, Bayes' theorem or analogical modelling; Global Causal Network);
    • World Data Framework (WorldDataArchitecture);
    • Global Knowledge Base (WorldKnowledgeNet, or WorldNet, embracing WordNet, ConceptNet, MindNet, TextNet, ImageNet, SpeechNet, ActionNet, PeopleNet, SocialNet, InterNet, CityNet, IndustryNet, NationNet,…PlanetNet, SpaceNet)
    • Domain Knowledge Base (DomainKnowledgeNet).

    The reality and quality of machine superintelligence are decided by the reality and quality of world’s data, models, algorithms, architectures and infrastructure, as the engine of any UAI cloud systems.

    The UAI ecosystem is emerging as the convergency/integration/synthesis/synergy of human collective intelligence and exponential technologies.

    The superintelligent AI model covers a conceptual view of an AI produced by the Expert Group on AI at the OECD.

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    The superintelligent AI model covers a conceptual view of an AI produced by the EU High-Level Expert Group on Artificial Intelligence (AI HLEG). 

    No alt text provided for this image

    The Machine Superintelligence is here, or How I finally created a superintelligence, interrelating reality, its models and data, with AI

    The author confirms a real plausibility and possibility of creating machine superintelligence as an artificial intelligence greatly outsmarting and outperforming the human minds and collective intelligence, and thus promising revolutionary technological, scientific, social and economic advances and deep implications for global governance and public policy.

    The superintelligence model discovery refutes a widely spread belief that “the transition to machine superintelligence will pose substantial, even existential, risks”; for it confirms that “AI is a general-purpose technology with transformative potential” and “the potential arrival of superintelligence in this century”.

    The precise mathematical definition of superintelligence construct is as follows: let W and D be two infinite universal sets, the universe of entities and the universe of data, called the source and target data, respectively.

    Superintelligent AI is symbolically as an universal triple <W, D, I>, where W denote the whole world of reality, with its entities, objects, states, properties, quantities, qualities, processes and relationships, or a universal set of entity variable

    D represents the whole world of data, data universe, with its classes and types, sets and elements, structures and patterns, or a universal set of data variables

    relates to global intelligence, with all its classes and kinds, universal intelligence, general intelligence, biological intelligence or computing intelligence or narrow intelligence, as ML and DL, or a universal set of intelligences.

    The Superintelligent AI is then formally encoded as a Global Intelligence Function (GIF) I, a process or a relation that associates each element w of a universal set W, the domain of the function, to a single element d of another universal set D (possibly the same set), the codomain of the function, the value of the GIF, the output, or the image of d by I, a function of the entity variable w:

    I: W→ D

    is a complex transformation or total function mapping the input elements or structures from W to the output data (elements, types, structures, patterns or relationships) over the global data space D, where the data processed as to world’s models and master algorithms.

    In all, GIF, covers all sorts of functions, maps, mappings, transformations, correspondences, or operators, or machines, applied in pure or applied mathematics or computer science.

    Superintelligent AI exists conceptually, virtually, digitally or physically, namely as in:

    ·        universal model or framework of reality with a virtually unlimited DDEPP (descriptive, deductive, explanatory, predictive and prescriptive) power, ordering the world knowledge and organizing all the world’s information.

    ·        universal intelligence code embracing all sorts of conceptual representations, intelligence processes, meaningful experience, codes and encodings, algorithmic, cognitive, natural language, semantic, textual, neural, as well as a digital programmed computing from machine codes to characters, numbers, symbols or signals to be intelligible for humans and machines;

    ·        intelligent operating systems, superintelligent digital platforms or general intelligence software applications, of any use cases in any domains for any intelligent tasks

    ·        AI hardware equipment, powerful AI chips, AI computing machines, quantum AI computers, superintelligent networks, as a global AI internet of things, superintelligent AI technology

    The present data format of machine superintelligence is in the content format. The intellectual property is classified as a trade secret in the documentary format of a corporate White Book:

    Global Artificial Intelligence as a Digital Superintelligence Platform: The Specifications on How to build Real Machine Intelligence

    That humanity is on the way to a machine superintelligence world was first predicted decades ago in our pioneering books and articles on universal/general/artificial intelligence:

    Encyclopedic AI: Global Knowledge Base (the Academy of Sciences, in Russian, 1989, Moscow)

    Introduction into Information World (the Academy of Sciences, in Russian, 1991, Nauka, Moscow)

    Abdoullaev, A., Creating Machines with Universal Intelligence. In Proceedings of the IASTED International Conference on Intelligent Information Systems. The Bahamas, The IEEE Computer Society Press, 1997

    Abdoullaev, A., The Machine Intelligence Based on MetaLingua. In Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing. Anaheim, Calgary, Zurich, IASTED/ACTA Press, 1998

    Abdoullaev, A., Artificial Superintelligence, Moscow, Russia; Ohio, USA, 1999

    USECS: Universal Standard Entity Classification Systems: The Catalogue of the World, 1717 pages, 2005;

    Reality, Universal Ontology, and Knowledge Systems: toward the intelligent world (Global IGI Publishing, NY, 2008)

    A Smart World: A Development Model for Intelligent Cities. Keynote.

    The 11th IEEE International Conference on Computer and Information Technology (CIT-2011)

    Why humanity is in an urgent need of AI, as a Real AI, a universal AI, a digital superintelligence, a superintelligent network, or global AI platform, NOW?

    There are 3 key humanitarian reasons:

    ·        To build a Global Scale Platform and General Purpose Technology

    ·        To create a digital AI platform for Everybody and Everything

    ·        To enable turning the Global Goals into a sustainable future for all

    193 countries joined forces and formed the United Nation’s Sustainable Development Goals, as the Global Goals, serving as a universal promise for sustainable future.

    Global AI makes a Global Scale Platform and General Purpose Technology for turning the Global Goals into reality to build a better future for people and planet by 2030.

    Global AI understands the world through the world’s data, making sense of Global Goals data on poverty, inequality, climate change, environmental degradation, peace and justice.

    The Global AI is aligned with the G20 AI Principles and the OECD AI Principles for Trustworthy AI.

    Design, development, deployment and decisive global implementation of Superintelligent AI are just the matter of time and smart big money.

    The economic payoffs of AI are hard to measure. Unlike PriceWaterhouseCoopers estimations that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030, in fact, the superintelligent AI is to multiply the $100 trillion global GDP.

    Creating the first superintelligence

    A digital superintelligence as Artificial Intelligence (ASI) or Real and True Machine Intelligence or simply AI is under development right now.

    This has been recognized by Musk: "We are rapidly heading towards digital superintelligence that far exceeds any human". "I think it's very obvious."

    "We have five years. I think digital superintelligence will happen in my lifetime, 100%."

    Machines were to attain general human intelligence, the machines would quickly become superintelligent. They speculate that a computer with general intelligence would be able to speedily read all existing books and documents, absorbing the totality of human knowledge.

    AI as a Superintelligent AI, an Artificial Superintelligence System (ASIS), or simply Machine Intelligence, is generating machine consciousness and self-awareness by spreading into zillions of computer servers, the internet of things, and smart applications all across the world.

    Its operations could be performed as a global, AI internet hierarchy of servers, mobile devices, drones, military satellites, war-machines, androids and cyborgs, and other computer systems, as well as digitized human brains.

    Whoever has doubt of the AI capacity should think of Chinese 'Sky Net' scanning China's population in just one second and the world's population in two seconds.

    Microsoft, which invested $1 billion in OpenAI to build artificial general intelligence (AGI) with economic benefits.

    OpenAI Charter states: "OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome".

    The idea is to partner to develop a hardware and software platform within Microsoft Azure which will scale to AGI.

    Second, “to create an AI that has super intelligence to create invention ideas with endless imagination” means to build a superintelligence model, as a globally distributed universal intelligence.

    It is the hardest human task ever, but realizable.

    Last, it could cost a completely different amount, $1 trillion, just to start, as far as it will upend the human economy.

    <Universal AI and how much might cost real AI model:>

    Global AI Platform Architecture

    Today's AI is a specialized, weak-minded AI tending to be simple and single-task oriented, designed to carry out one particular job, as self-driving cars or hospital operating rooms, video games and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it pattern-matching the answers for you. Their neural network are mechanically trained on thousands of hours labeled audio data, rote learning to associate sounds with certain words and phrases. 

    Real, True AI demands a cross-disciplinary approach based on philosophy, logic, semantics, knowledge representation, mathematics, statistics, computer science, linguistics, psychology, and more.

    Due to its inherent generality, the applications for AI are endless, and its technology can be applied to many parts of life, different sectors and industries. It is thus being used across different industries including agriculture and manufacturing, finance and healthcare, transport and telecommunications, public administration and the military.

    Nevertheless, with all its hype and high talks, AI is essentially wanting its general theory, universal model and complete architecture, as outlined below:

    Intellectual Human-Computing Platform = Real Intelligence/True AI =

    • World-Data-Mind Model/Intelligence/Knowledge/Learning/Cognition/Thought/Decision/Self-Consciousness/Action +
    • World's Data Computing Framework + Master Algorithm +
    • Symbolic AI/Ruled-based techniques, models, algorithms, applications +
    • Sub-symbolic AI/Machine Learning +ANN + DNN/statistic learning-based computational techniques, cloud platforms, models, algorithms, applications, as listed below by the narrow Artificial Intelligence led by the US tech giants, such as Google, Microsoft, Amazon, and giant Chinese brands as Baidu, Tencent and Alibaba.

    Google AI

    About – Google AI

    Microsoft AI

    Microsoft Artificial Intelligence

    Amazon AI

    AI with AWS Machine Learning

    Facebook AI

    Facebook AI

    IBM AI

    Apple AI

    Join the Apple Machine Learning and AI team and make an impact with the products you create and the research you publish.

    Baidu AI,

    Alibaba Cloud Intelligence Brain, “an ultra-intelligent AI Platform for solving complex business and social problems”

    Tencent AI. WeChat AI: machine learning, computer vision, speech recognition, and natural language processing, and their applications in Game, Social, Content and Platform AI.

    Note that Alibaba Cloud Intelligence Brain is advertised as "an ultra-intelligent AI Platform for solving complex business and social problems".

    The superintelligent AI models are able to a comprehensive deep understanding and general transfer learning, being not an expert AI or a general AI, but an expert-generalist:

    • deconstructs world knowledge into fundamental principles and mental models
    • reconstructs the fundamental principles in new fields, domains, use cases, and applications
    • demonstrating comprehensive deep understanding and general transfer learning

    AI is about Data, Intelligence, and Reality, or how the World is to be represented in the Data Processing Systems to demonstrate learning and reasoning and intelligent behavior.

    ML is about Data Representation, or how the Data is to be represented in the Data Processing Systems as ANNs to demonstrate automated data learning/feature representation...

    ML is about the study and construction of algorithms that can learn from and make decisions or predictions on data, through building a mathematical model from input data, as training, test, and validation sets.

    Machine learning algorithms are designed to optimize for a cost/loss function, having no intelligence, understanding or reasoning.

    So, it is

    • predictive analytics statistical technique, together with data modeling, deep learning algorithms and data mining, capturing relationships between explanatory variables and the predicted variables from past occurrences to interpolate/predict the unknown outcome
    • a set of computer algorithms that improve automatically through data pattern recognition minimizing the sum of the squared residuals
    • predictive analytics that analyze current and historical facts to make predictions about future or otherwise unknown events
    • machine statistics extracting information from data and using it to predict trends and behavior patterns...
    • a brute-force big data processor fitting its parameters to the many examples that it experiences and failing to extract meaning from data and experience, at extracting meaning from the world.

    The reason the weak AL/ML/DL/ANN community has adopted the mega-scale, brute-force mindless statistical approach is that it works; it has yielded better performance than any alternative, symbolic AI algorithms. Statistical ML could be necessary but insufficient, and will get you just to the unlimited expenses of resources, human, financial and natural.

    Most curve-fitting pseudo-AI tools available today sold as focused on predicting, identifying, or classifying things, a rote "learning from data/experience". The GPT-3 text generator promises even to go far beyond, creating text including essays, paragraphs, and articles just like humans, but at a much faster pace, with prospects to write code, improve chatbots, create news articles, design websites, and do much more.

    All is with zero real understanding and intelligence, just being trained for a mechanical memorizing, rote learning, on 175 billion parameters/weights compared to 1.5 billion parameters for the GPT-2.

    It is plain that the maths is behind today's Big Tech AI of weak/narrow of machine learning techniques, deep learning methods and ANNs.

    No alt text provided for this image

    As can be seen, DNNs are built on calculus and some statistics.

    No mind, no learning, no cognition, no understanding, no intelligence, just statistics, curve-fitting, the Laplace-old cost & loss & regret function or profit/reward/utility/fitness optimization function and error calculation with backpropagation, or a simulation/fake AI...

    Most people are happy to confuse a weak/narrow/false AI with a strong/general/true AI.

    In fact, there are 5 models of AI increasing in complexity and reality, as in:

    • Logical/Symbolic AI, as the Logic Theory Machine, if-then expert systems and RPA, dubbed as GOFAI;
    • Statistic/Subsymbolic, as ML/DL/ANN Narrow/Weak AI;
    • AGI, simulating the human intelligence in general;
    • Synthetic AI, as synthetic drugs;
    • Real True AI as a DSI, basing on the world's model of reality, its prime entities, relations and fundamental laws, as the knowledge and reasoning computing framework.

    Real AI vs. Fake AI: Global AI vs the global AI Market

    Global AI market is monopolized by few multinationals. Google , AmazonMicrosoftIBM with the BAT-triada all offering automated machine learning services in the cloud, dubbed as AI as a Service (AIaaS).

    Their ML hardware, cloud and algorithmic solutions will power your conversational agents and chatbots, speech, NLP and semantics, vision, specialized algorithms programs.

    The global AI value chain could be as described as below:

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    The AI value chain — who will make money with AI? The companies noted are representative of larger players in each category but in no way is this list intended to be comprehensive or predictive. © Best Practice AI Ltd

    (1) AI chip and hardware makers who are looking to power all the AI applications that will be woven into the fabric of organisations big and small globally;

    (2) the cloud platform and infrastructure providers who will host the AI applications;

    (3) the AI algorithmic and cognitive services building block makers who provide the vision recognition, speech and deep machine learning predictive models to power AI applications;

    (4) enterprise solution providers whose software is used in customer, HR, and asset management and planning applications;

    (5) industry vertical solution providers who are looking to use AI to power companies across sectors such as healthcare to finance;

    (6) corporate takers of AI who are looking to increase revenues, drive efficiencies and deepen their insights;

    (7) nation states who are looking to embed AI into their national strategies and become AI enabled countries.

    It all has little to do with True, Actual or Real AI, but with AutoML, automated machine learning and statistical data computing, today's "AI".

    We have two opposite classes/kinds/types/concepts/models of AI:

    • True, Actual or Real AI
    • False, Fictitious or Imaginary, i.e. today's "AI".

    The today's "AI" is presented by what the Big Tech and global social media platforms are hardly pushing, it’s Narrow/Weak AI/ML/DL, like as“Cloud DL/AI Platforms”.

    Artificial Intelligence or Digital Superintelligence as a Global Scale Platform and General Purpose Technology

    Artificial Intelligence or Digital Superintelligence is NOW emerging as the integration/synthesis/synergy of human collective intelligence and exponential technologies:

    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,

    brain-computer interfaces (BCI),

    additive manufacturing and 3D printing,

    blockchain technology,

    autonomous vehicles,


    alternative energy systems,

    biotechnology, digital medicine,

    quantum computers, etc.

    A superintelligence, hyperintelligence, or superhuman intelligence is an aggregate entity, rather than some “hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds”.

    Again, AI is NOT about simulating human intelligence processes by machines, or computer systems, intelligent machines that work and react like humans.

    It is the World Feature Engineering, what makes a core part of Real AI R & D & I & I, as much as the feature engineering/data representation makes the core of automated machine learning and deep learning.

    Machines can think, act and react only if they have abundant data relating to the world, turned to information and knowledge, predictions and decisions, actions and performances.

    Real Artificial intelligence must have access to entities, categories, properties and relations between all of them to implement the World Feature Engineering.

    AI for Everybody and Everything (AI4EE): Universal Artificial Intelligence

    What one is to learn for Superintelligence

    I had to combine a wide-ranging knowledge over a broad spectrum of disciplines around AI - natural sciences, social sciences cognitive sciences and technical sciences and engineering and computing science and philosophy or ontology - into a comprehensible whole.

    I had to deep learn, study and explore:

    ·        the most of Britannica, Macropaedia, Knowledge in Depth, the Great Books of the Western World, Synopticon I-II

    ·        The best of philosophical works from Aristotle’s books till Bunger’s general system philosophy.

    ·        The best of published works on philosophical ontology and computing ontology and human knowledge integration inquiries

    ·        The best of published works on reality and causality and intelligence

    ·        The best of AI research papers from the symbolic AI to statistical Machine Learning.

    ·        The best research on the nature of reality, universal theories, mental models of reality, and unifying schemas of the world, mind and data representations.

    Write great books to spread new knowledge and big ideas

    Introduction into Information World (the Academy of Sciences, in Russian, 1991, Nauka, Moscow)

     Artificial Superintelligence (Browling Green University, USA, 1999)

    Reality, Universal Ontology, and Knowledge Systems: toward the intelligent world (Global IGI Publishing, NY, 2008)

    Science and Technology XXI: Wise World Monographic Series

    Azamat Sh. Abdoullaev, Physics and Technology of the 21st Century, New Physica; EIS; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-2-9

    Azamat Sh. Abdoullaev, Disrupting Modern Science, Technology and Engineering with Wisdom Science; EIS; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-7-4

    Azamat Sh. Abdoullaev, Wise World Wide Web and Technological Singularity; EIS ; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-4-3

    Azamat Sh. Abdoullaev, Wise Encyclopedia for Minds and Machines; EIS; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-5-0

    Azamat Sh. Abdoullaev, NEW WISDOM BOOK, Universal Standard Entity Classification System, USECS; EIS; EU, Russia, 2015; ISBN 978-9963-8421-8-6

    Azamat Sh. Abdoullaev, Neapolis Smart Eco City: A Development Framework for Sustainable Cities; EIS; EU, Russia, 2010; ISBN 978-9963-9958-0-6

    Azamat Sh. Abdoullaev, Future Communities Guide: Smart Cities and New Urban Revolution; EIS; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-6-7

    Azamat Sh. Abdoullaev, Project Russia 21_Wise Intelligent Superpower Power; EIS; EU, Russia, 2016; ISBN 978-5-600-01518-0 (in Russian)

    Azamat Sh. Abdoullaev, Wise Nations, Powers and Superpowers; EIS; EU, Russia, 2016; ISBN set 978-9963-2202-1-2; ISBN 978-9963-2202-3-6

    Azamat Sh. Abdoullaev, Wise World vs. Ill World; EIS; EU, Russia, 2016

    To perform trans-disciplinary R&D Projects: Global AI Knowledge Base

    USECS: Universal Standard Entity Classification Systems: The Catalogue of the World, 1717 pages, 2005;

    To create an I-World Construct: Constructing a Smart World of the Tomorrow

    I-WORLD™, IWORLD™, iWORLD™, iWorld™: AI World: Intelligent, Innovative, Interconnected, Instrumented, Inclusive, Green WORLD: Smart CONTINENTS, COUNTRIES, CITIES, AND COMMUNITIES

     Special part of the I-World Construct is made by I-Nation Development Strategy/Plan (i-Nation) and Smart Eco City Strategy/Plan, including such unique trademarks and brands as:

    • I-America™ (Smart Green America™)
    • I-Europe™ (Smart Green Europe™)
    • I-China™ (Smart Green Europe™)
    • I-Japan™ (Smart Japan™)
    • I-Russia™ (Smart Green Russia™)
    • I-Britain™ (Smart Britain™)
    • I-Germany™ (Smart Germany™)
    • I-City™ (Smart Sustainable Cities™; Smart Eco City™; Intelligent Green Cities™)

    The i-nation construct is to make a core of any AI national strategy, as pictured below:

    No alt text provided for this image

    Machine Superintelligence as a classified discovery of discoveries

    Presently, the outcome (discoveries, models, algorithms and inventions) is classified as trade secrets, with the following AI components:

    ·        Global Data Platform for all data types and data formats, classified, 2019

    ·        Computing Ontology and Causal Master Algorithms, classified, 2019

    ·        Global AI Platform for the Symbolic AI and non-Symbolic ML: Specifications, classified, 2019

    To advance Global AI4EE, Artificial Intelligence for Everybody and Everything

    The Universal AI Model is a must for the leading AI corporations and state powers, as the EU, Russia, USA, China, as well as the UN as promoting 17 Sustainable Development Goals.

    The investment cost of the Universal AI Model is Euro 1 trillion ONLY, what is 1000 times exceed Microsoft’s investment of $1bn for a prospective AGI R&D.

    Public Knowledge Spreading

    I have answered 1000+ questions on the AI Quora, 6m+, being the most viewed author in General AI Group, 500K+, and Artificial Superintelligence Group, 100K+ 

    AI’s SOTA

    A common understanding of superintelligence is rather poor and naïve, biased and fragmentary, what one can see from many TED talks, newspaper articles, books and interviews.

    “Superintelligence” is a flawed concept and shouldn’t inform our policy decisions.

    Dr. Bostrom, Dr. Russell and other writers argue that even if there is just a small probability that such superintelligent machines will emerge in the foreseeable future, it would be an event of such magnitude and potential danger that we should start preparing for it now. In Dr. Bostrom’s view, “a plausible default outcome of the creation of machine superintelligence is existential catastrophe.”

    Scared of superintelligent AI? You should be, says neuroscientist and philosopher Sam Harris -- and not just in some theoretical way. We're going to build superhuman machines, says Harris, but we haven't yet grappled with the problems associated with creating something that may treat us the way we treat ants.

    How we’ll create the first Artificial Superintelligence: Future of artificial intelligence

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    Today we have Artificial (narrow) Intelligence. In the future we might expect machines to demonstrate the same level of intelligence of humans (Artificial General Intelligence) and thereafter to take the lead with a human-machine convergence, immediately followed by humans 2.0 and Artificial Super Intelligence. Timeline by Reimagining the Future.

    Superintelligence Resources

    How Do We Create Digital Superintelligence?

    Why AI is to take over the human world

    Artificial Intelligence or Digital Superintelligence as a Global Scale Platform and General Purpose Technology

    How to Regulate the Big Tech fake AI: "AI and ML Falsification Act"

    How to remedy Fake AIs and build Real AI World: True Trustworthy AI

    What is the (true) nature of reality?

    Global Artificial Intelligence (GAI): Narrow AI, Applied AI, ML&DL, Strong AI, Full AI, AGI, Global AI, Real AI, Superhuman Intelligence

    Artificial Intelligence Science and Technology, Next Generation: Get Ready for AI GOD Applications

    Good, I.J., Speculations concerning the first ultraintelligent machine. Advances in computers, 1965; 6(99), pp. 31-83.

    Nick Bostrom, Superintelligence: Paths, Dangers, Strategies; 2014

    Nick Bostrom, Allan Dafoe, Carrick Flynn, Policy Desiderata for Superintelligent AI: A Vector Field Approach;

    Brynjolfsson, E. and McAfee, A., The second machine age: Work, progress, and prosperity in a time of brilliant technologies. 2014, Vancouver: WW Norton & Company.

    Andrew McAfee and Erik Brynjolfsson, Machine Platform Crowd: Harnessing Our Digital Future (New York: Norton, 2017).

    PriceWaterhouseCoopers, “Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise?” 2017.

    François Chollet, The implausibility of intelligence explosion,

    Elon Musk's Final Warning About AI: Should We Create a Digital Superintelligence?

    Elon Musk has warned about the dangers of AI in many occasions. He is one among many public thinkers who have expressed concerned about the risks involved in artificial intelligence. Particularly, a digital Superintelligence as Elon calls it. While artificial intelligence systems continue to improve, they also raise a fundamental question about the survival of our species.

    A Superintelligence would be capable of rapid learning and unlimited memory, making it a potentially superior being. It is difficult to study an AGI, but the possible results are worrying. A Superintelligence might have a rapid growth period, taking over every computer system and reducing the human race to a small and inconsequential presence.

    The 17 sustainable development goals (SDGs) to transform our world. The Sustainable Development Goals are the blueprint to achieve a better and more sustainable future for all. They address the global challenges we face, including poverty, inequality, climate change, environmental degradation, peace and justice.

    EIS Encyclopedic Intelligent Systems

    EIS Encyclopedic Intelligent Systems is the leading innovative business enterprise dealing with Smart Territories and Intelligent Communities, Smart Continents, Countries, Cities and Communities,

    EIS Encyclopedic Intelligent Systems Ltd is the first GLOBAL AI Company.

    EIS Encyclopedic Intelligent Systems Ltd is to make our world and its countries, cities and human settlements smart, intelligent, inclusive, safe, resilient, green and sustainable

    EIS Encyclopedic Intelligent Systems, and its owner, is the creator of the concept of Intelligent World, having the major features and parameters as:

    All connected;

    All digital;

    All intelligent (Everything will become intelligent, and our world as a whole will be intelligent, including its territories, geopolitical communities and cities).

    Artificial Superintelligence as the next big thing

    EIS developed the first real model of the Universal AI, including the following elements: 

    Machine World Model;

    Master Algorithm;

    World Data Framework;

    Global Knowledge Base World.Net

    Universal Intelligent Platform I-World

    Universal Artificial Intelligence, and how much might cost Real AI Model

    The First GLOBAL AI Company: EIS Encyclopedic Intelligent Systems ltd

    THE EIS I-WORLD PLATFORM: Future World Technology Roadmap

    WORLD 1.0 (Industrial World) :: Global Community 0.0 > Society 1.0> Nation 1.0 > City 1.0 > Science 1.0 > Technology 1.0 > Industry 1.0 > Infrastructure 1.0 > Network 1.0 > Telecom 1.0 > Internet 1.0 > Web 1.0 > Service 1.0 > Government 1.0 > Medicine 1.0 > Human 1.0 > Intelligence 1.0 >…Space 1.0

    WORLD 2.0 (Information World) :: Global Community 2.0 > Society 2.0 > Nation 2.0> City 2.0 > Science 2.0 > Technology 2.0 > Industry 2.0 > Infrastructure 2.0 > Network 2.0 > Telecom 2.0 > Internet 2.0 > Web 2.0 > Service 2.0 > Government 2.0 > Medicine 2.0 > Human 2.0 > Intelligence 2.0 >…Space 2.0

    WORLD 3.0 (Smart World) :: Global Community 3.0 > Society 3.0 > Nation 3.0> City 3.0 > Science 3.0 > Technology 3.0 > Industry 3.0 > Infrastructure 3.0 > Network 3.0 > Telecom 3.0 > Internet 3.0 > Web 3.0 > Service 3.0 > Government 3.0 > Medicine 3.0 > Human 3.0 > > Intelligence 3.0 > …Space 3.0

    WORLD X.0 ::

    Global Community X.0 >

    Society X.0 >

    Nation X.0>

    City X.0 >

    Science X.0 >

    Technology X.0 >

    Industry X.0 >

    Infrastructure X.0 >

    Network X.0 >

    Telecom X.0 >

    Internet X.0 >

    Web X.0 >

    Service X.0 >

    Government X.0 >

    Medicine X.0 > Human X.0 >

    Intelligence X.0 >…Space X.0

    The First GLOBAL AI Company: EIS Encyclopedic Intelligent Systems ltd


    The Global Artificial Intelligence Is Here

    It is to our common advantage if the GAI becomes a distributed intelligence with a large and diverse set of humans providing guidance.

    But why build a new sort of GAI at all? Creation of an effective GAI is critical because today the entire human race faces many extremely serious problems. The ad-hoc GAI we have developed over the last four thousand years, mostly made up of politicians and lawyers executing algorithms and programs developed centuries ago, is not only failing to address these serious problems, it is threatening to extinguish us…

    But because existing multinational governance systems have failed so miserably, such an approach may require replacing most of today's bureaucracies with "artificial intelligence prosthetics", i.e., digital systems that reliably gather accurate information and ensure that resources are distributed according to plan…

    In my opinion, it is critical that we start building and testing GAIs that both solve humanity's existential problems and which ensure equality of control and access. Otherwise we may be doomed to a future full of environmental disasters, wars, and needless suffering.

    Alex "Sandy" Pentland

    Professor of Computer Science, MIT; Director, MIT Connection Science and Human Dynamics labs; Author, Social Physics

    Dr. Azamat Abdoullaev, EIS Encyclopedic Intelligent Systems, EU, Russia

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