What Is Intelligence?
A General Theory of Artificial Intelligence
Published on 7. August 2025
156 pages
978-2-7598-3726-7 (ISBN)
Description
What is Intelligence? What is Artificial Intelligence (AI)? Can AI develop autonomous consciousness? Will AI surpass humans in all areas in the near future? Should humans prepare to escape Earth to avoid being dominated by AI machines?These questions have sparked significant public debate, especially since the release of ChatGPT by OpenAI in 2022. Widespread discussions and concerns about AI's future role in society have led to growing uncertainty, with some fearing that AI might eventually control or harm humanity.As AI researchers, the authors of this book feel it is their responsibility to address these concerns. They aim to provide clear answers based on deep analysis and expert knowledge, helping people to better understand AI's capabilities and limitations. Their goal is to dispel unfounded fears and encourage the responsible development and use of AI for the benefit of all.The insights presented in this book are grounded in thoughtful consideration and rigorous research, offering a balanced perspective on the future of AI and its impact on society.
More details
Edition
Digital original
Language
English
Place of publication
Les Ulis
France
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
3,18 MB
ISBN-13
978-2-7598-3726-7 (9782759837267)
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Schweitzer Classification
Persons
Contributor: Yixin Zhong Yixin Zhong, Professor at Beijing University of Posts and Telecommunications, has focused on information science and artificial intelligence research and teaching for half a century. --- Contributor: Huacan He Huacan He, Professor at Northwest Polytechnical University, has dedicated his research career to computing, logic, and AI. --- Contributor: Peizhuang Wang Peizhuang Wang, Professor at Beijing Normal University and Liaoning University of Engineering and Technology, is specialized in statistical mathematics and factor space theory. --- Contributor: Yong Shi Yong Shi, Chair Professor at the University of Chinese Academy of Sciences, is a leading expert in big data analytics, data mining, knowledge management, and the digital economy. --- Contributor: Xiangfu Meng Xiangfu Meng, Professor at Liaoning Technical University, is dedicated to AI model research and its applications in medical healthcare. --- Contributor: Yi Qu Yi Qu is apostdoctoral research fellow at the University of Chinese Academy of Sciences. --- Contributor: Yunong Wang Yunong Wang is a Ph.D. candidate at the University of Chinese Academy of Sciences.
Content
- Intro
- What Is Intelligence? A General Theory of Artificial Intelligence
- Introduction
- Contents
- Paradigm Revolution in the Field of Intelligence
- New Explanation of Basic Concepts
- Human Intellectual Ability
- Human Wisdom
- Human Intelligence
- Artificial Intelligence
- New Exploration of Scientific Laws
- Science and Technology: Why Does It Emerge (Starting Point)? How Does It Develop (Process)? What Role Will It Perform (End Point)?
- Evolutionary Patterns of Human Capacity Expansion Needs
- Characteristics of the Era of Scientific and Technological Development
- Paradigm Theory I: New Definitions of Concepts
- Paradigm Theory II: The Paradigm Formation Period
- Paradigm Theory III: Mismatch of Paradigm During the Paradigm Formation Period
- Paradigm Theory IV: The Implementation Framework of the Paradigm Revolution
- The Claim ``AI Can Surpass Humans in All Aspects'' Is Not Valid
- Artificial Intelligence: Paradigm Mismatch and Paradigm Revolution
- The AI Research So Far: Paradigm Mismatch
- Steps in Implementing the Paradigm Revolution in AI
- The First Step in the Paradigm Revolution in AI: Summarizing and Establishing the Paradigm for the Information Discipline
- The Second Step in the Paradigm Revolution: Constructing a Global Model of AI
- The Third Step in the Paradigm Revolution: Exploring Research Approach in AI
- The Fourth Step in the Paradigm Revolution in AI: Precision in the Academic Structure of AI
- The Fifth Step in the Paradigm Revolution in AI: Precision in the Fundamental Theory of AI
- The Sixth Step in the Paradigm Revolution in AI: Reconstructing a New Theory of AI
- Implementing the Universal Intelligence Generation Mechanism and Creating the General AI Theory
- The Principle of Perception (and Attention): Conversion from ``Object Information'' to ``Perceptual Information''
- The Principle of Cognition: Conversion from ``Perceptual Information'' to ``Knowledge''
- The Principle of Memory Expression: Comprehensive Information and Comprehensive Knowledge Representation of the Memory Base
- The Principle of Strategy Formulation: Conversion from ``Perceptual Information - Knowledge - Goal'' to ``Strategy''
- The Principle of Strategy Execution: Conversion from Intelligent Strategy to Intelligent Action and Optimization of the Strategy
- Universal Logics
- The Basic Law of Logic's Development
- The Current Direction of Logic Development
- Basic Parts in Logic
- Basic Properties of the Object of Logic
- The Basic Property of the Objective World Is Evolution
- Analysis of the Basic Properties of the Subjective World
- Intelligence Can Only Be Formed and Evolve in a Realistic Environment
- Research and Practice in AI Have Proven that It Requires Universal Logics Support
- The Original Intention of Establishing the Discipline of AI
- Over 70 Years of Practical Experience in AI Research
- Giving Computers More Intelligence Factors
- AI Research Urgently Needs Logical Paradigm Revolution
- Propositional Universal Logics Theory
- Theoretical Framework of Propositional Universal Logics
- An Effective Way to Achieve Propositional Universal Logics
- The Specific Expansion Process of Propositional Universal Logics
- How to Apply Positional Universal Logics
- Robustness Criteria Using Propositional Universal Logics
- Method for Determining the Parameters of the Logical Operation Model
- Logical Support for Intelligent Generation Mechanism
- Propositional Universal Logics and Deep Neural Network
- Summary
- Factor Space
- Factor Space Is a Mathematical Product of the Paradigm Revolution in Intelligence Research
- Definition and Properties of Factor Space
- Factors Are Generalized Variables
- Definition of Factor Space
- Background Base
- Factor Spectrum
- Knowledge Growth Expression
- Definition of Factor Spectrum
- Root and Derivative Factors
- Factor Pedigree and Factor Space Vine
- Factor Encoding - the DNA of Knowledge Ontology
- Factor Space Is the Basis for Revolution of Cause and Effect
- Pearl's ``Revolution of Cause and Effect'' Theory (Pearl et al., 2018)
- The Core Idea of Causality Analysis
- Factors Are Elements of Causality Analysis
- Attribute Association and Factor Correlation
- General Principles of Causality Induction
- Correlation Determines Causality
- Causality Must be Uncovered from the Correlation Theory of Probability Statistics
- Causality Triangulation Method
- Factor Space Theory Is the Mathematical Foundation of Information and Intelligence Science
- Factor Spaces Provide a Unified Descriptive Platform for All Branches of Intelligent Mathematics
- The Basic Problem of Object Distinguishing
- Automatic Generation of Concepts
- Basic Problem of Causality Induction
- Rough Calculation of Sweep Class and Explicit and Implicit Algorithm Using Machine Learning
- Tentative Algorithm for Supporting Vector Sets
- Factor Space Is a Mathematical Tool for Intelligent Incubation
- Description of Perception Process
- Intelligence Incubation Project
- Summary and Outlook
- Summary of Basic Principles
- A Brief Review of Current AI Research
- Outlook
- Bibliography
