Researchers EE, CS, NETWORKS

Researchers EE, CS, NETWORKS

Research for MS/PhD or for a generation of Knowledge/Wisdom Machines

Thursday, January 1, 2009

Processing of Knowledge and Wisdom

Technical Contents of the Two most recent books are presented for research students and research scientists in Computer Science, Electrical Engineering, Networks, and Telecommunications.
Meant mainly for MS and Ph.D. Students in CS, EE, and Networks.
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Computational Framework for Knowledge
Integrated Behavior of Machines
Wiley Interscience, 2009

Foreword

"This is a very unusual book dealing with a very unusual subject.
"We are all familiar with the filtering and processing of signals according to certain given criteria, such as selecting a frequency band out of a communications signal, reducing unwanted noise or other artifacts from a given electrical signal, or filtering out certain colors from a light signal. Information theory, invented by Claude Shannon some 60 years ago, went a step further. Shannon defined mathematically the information contained in communication signals, by formulating a mathematical measure for information which he called entropy (reduction of uncertainty in a given information message).With this mathematical formulation he was able to process and quantify information and to formulate the maximum quantity of information that a given channel can transmit. It is important to note here, that Shannon's concept of information is entirely independent of the 'knowledge' that is contained in his information signal.
"Prof. Syed Ahamed has now gone a decisive step further, and suggests something that has not been suggested in so much detail ever before: the 'filtering' of knowledge, according to criteria postulated by the receiver of a stream of information conveying this knowledge. Since the 'quality' or 'value' of knowledge is by its very nature subjective, Prof. Ahamed introduces methods of formulating and quantifying the parameters necessary to filter knowledge according to the value system of the person at the receiving end of that knowledge. In the hands of a lesser expert this endeavor may well seem Utopian. However, Prof. Ahamed's credentials are most impressive, and it is no exaggeration to say that if anyone can tackle this project with some hope of success, which may essentially mean starting an entirely new discipline, then Prof. Ahamed is that person.
"Syed Ahamed is a well recognized communications and systems expert with many years of experience at Bell Labs, as well as a university professor in the same field. He is also well versed in computer science and mathematical methods which he has used in numerous purely technical areas, and documented in several text books. What makes him unusual, and indeed exceptional, is that he is also a quasi-philosopher and humanist, who has devoted much of his life to contemplating problems of society and how to alleviate them. His intentions in this respect are very pure and idealistic; however they are tempered by the practical and realistic view of an engineer and scientist.
"This latter point, namely the genuine and benevolent intentions of Syed Ahamed, is very important, because the 'filtering of knowledge' – if it can be done successfully – can of course be misused by every propagandist, tyrant, and dictator anywhere on this planet. This becomes clear when we realize that the object of this book is to go far beyond what we know today as simple ' SPAM filtering' and the like. However, I feel that if the filtering and manipulation of knowledge can be done – and Prof. Ahamed's book will convince us that there is a high likelihood that it can - then it will be done by someone, and possibly by someone much less qualified to do so than he. Thus, the apprehensions that may be expressed by a critic of the subject of this book, namely the manipulation of knowledge, are similar to the apprehensions that might have been expressed at the time of the invention of matchsticks, razor blades, or any other of the items that can be used for the benefit or the detriment of mankind – depending on who lays their hands on them
"Among the highlights of this book, that define the novelty of its contents, are (i) that it combines philosophical, societal, and artificial-intelligence concepts with those of computer science and information theory, and (ii) that knowledge is treated as a mathematical object-based entity. Furthermore, the book tries to cope with the 'knowledge explosion' (as exemplified, for example, by the Internet, Google, and Wikipedia) by letting machines (i.e. computers) do the processing, classifying, and prioritizing of available information. Because of the immense amount of available information, these tasks are considered by the author as too formidable and insurmountable by humans without the help of machines.
"This realization is, in fact, one of the core motivations of the author for writing the book, namely, in his words, to 'disentangle the gigantic knot of information and knowledge available on a global scale via the Internet and computer communications'. Being an engineer and scientist, and more specifically an expert in computer science and electrical communication systems, Prof. Ahamed is also a humanist, philosopher, and poet. These are unique qualifications that entitle him to tackle the formidable task at hand. To do so, he introduces new concepts such as that of 'wisdom machines' that interact with humans. He claims that 'information is in the domain of machines, knowledge in the domain of humans'. The 'forces of society' are broken down into a 'triangle of knowledge' consisting of the three corners science, economics, and technology, much as the 'color triangle' used in the theory of color (as used for example in color television) has the corners red, green, and blue. He introduces these 'forces of society' in order to quantify, classify, and combine the characteristics of knowledge in terms of 'Verb Functions' and 'Noun Objects'. With newly-defined terms such as these, he feels confident that 'purifying the contents of embedded knowledge suddenly appears as a distinct scientific feasibility'.
"This book has the potential of becoming a 'must read' for a vast readership, including all scientists and engineers in the information technology field, but also psychologists, sociologists, people studying public communications, journalism, advertising, and more. The subject is both very original and highly ambitious. Sooner or later, with the ongoing information revolution as typified by the Internet Age, someone was bound to tackle the problem of 'Knowledge Filtering', and there couldn't be a better choice than Prof. Ahamed to start the process going."
Preface written by

Prof. George S. Moschytz
Head, School of Engineering,
Bar-Ilan University, Israel.
December 2008

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Foreword
PREFACE
Introduction
Chapter 1 New Knowledge Environments
CHAPTER SUMMARY
1.1 THE NEED TO KNOW
1.1.1 Global Power of Knowledge
1.1.2 Scientific Aspects
1.1.3 Wealth Aspects
1.2 ROLE OF TECHNOLOGY
1.2.1 Three Major Contributions
1.2.2 A String of Secondary Contributions
1.2.3 Peripheral Contributions
1.3 KNOWLEDGE AND WEALTH
1.4 EVOLVING KNOWLEDGE ENVIRONMENTS
1.4.1 Components of Knowledge
1.4.2 The Processing of Knowledge
1.5 STRUCTURE AND COMMUNICATION OF KNOWLEDGE
1.5.1 Velocity of Flow of Knowledge
1.5.2 Truisms in Knowledge Domain
1.5.3 Philosophic Validation of Knowledge
1.5.4 Scientific Principles in Knowledge Domain
1.5.6 Aspects of Knowledge
1.6 INTELLIGENT INTERNET AND KNOWLEDGE SOCIETY
1.6.1 Four Precursors of Modern Wisdom
1.6.2 Knowledge Bases to Derive Wisdom
1.6.3 Role of National Governments
1.6.4 Universal Knowledge Processing Systems
1.6.5 Educational Networks
1.6.6 Medical Networks
1.6.7 Anti-Terrorism Networks
1.7 KNOWLEDGE NETWORKS
1.7.1 Evolution of Knowledge Networks
1.7.2 Knowledge Network Configuration
1.8 CONCLUSIONS
REFERENCES
Chapter 2 Wisdom Machines
CHAPTER SUMMARY
2.1 MANY FLAVORS OF WISDOM
2.2 THREE ORIENTATIONS OF WISDOM
2.2.1 Absolute Wisdom
2.2.2 Materialistic Wisdom
2.2.3 Opportunistic Wisdom
2.2.4 Needs And Wisdom
2.2.5 What Are Wisdom Machines
2.3 OPTIMIZATION OF WISE CHOICES
2.3.1 Derived Axioms
2.3.2 Priming Of Wisdom Machines For Directional Axioms
2.4 THREE LEVEL FUNCTIONS
2.4.1 Level I - Access And Administrative Functions
2.4.2 Level II - Linkage, Scientific And Statistical Functions
2.4.3 Level III – Human Authentication
2.5 KNOWLEDGE MACHINES BUILDING BLOCKS
2.5.1 What Are Knowledge Machines
2.5.2 Knowledge Machines Based Wisdom Machines
2.5.3 Sensor-Scanner Based Wisdom Machines
2.5.4 Bus Configurations and Switch Locations
2.6 MACHINE CLUSTERS
2.6.1 Single Wisdom Single Machine (SWSM) Systems
2.6.2 Single Wisdom Multiple Machine (SWMM) Systems
2.6.3 Multiple Wisdom Single Machine (MWSM) Systems
2.6.4 Multiple Wisdom Multiple Machine (MWMM) Systems
2.7 FROM WISDOM TO BEHAVIOR
2.8 ORDER, AWARENESS, AND SEARCH
2.9 CONCLUSIONS
REFERENCES
Chapter 3 General Theory of Knowledge
CHAPTER SUMMARY
3.1 A BASIS FOR THEORY OF KNOWLEDGE
3.2 COMPREHENSION, NATURE, AND KNOWLEDGE
3.2.1 A Functional Approach
3.2.2.Incremental Changes
3.2.3 Elemental Convolution and Knowledge Operations (kopcs)
3.3 CENTRAL PROCESSING AND KNOWLEDGE PROCESSING
3.4 ACCUMULATION OF INFORMATION, KNOWLEDGE, AND WISDOM
3.5 THE ENHANCED KNOWLEDGE TRAIL
3.6 SEQUENCING OF EVENTS AT NODES
3.7 TRANSITIONS AT I, K, C NODES
3.8 TRANSITION MANAGEMENT AT NODES
3.9 SIMPLIFIED TRANSITION DIAGRAM
3.10 ORIGIN AND DESTINATION
3.10.1 Nature (N), Origin of Knowledge Trail
3.10.2 Two Destinations of Knowledge Trail
3.10.3 Multiple Feedbacks along of Knowledge Trail
3.10.4 Dynamics of Knowledge in Societies
3.10.5 I, K, C, W and E Bases to Replace Nodes
3.10.6 Nodal Forces in Societies
3.10.7 Summary of Sociological Forces on Nodes
3.10.8 Multiplier Effects at Intermediate Nodes
3.10.9 Implications of Knowledge Equations
3.11 THE ENTROPY OF KNOWLEDGE
3.11.1 The Change of Entropy
3.11.2 The Duration for Change of Entropy
3.11.3 No Prior Knowledge – No Change in Entropy
3.11.4 No Knowledge Process – No Change in Entropy
3.11.5 Examples of Prevalent Knowledge Processes
3.11.6 Generalization of Knowledge Processes
3.12 CONCLUSIONS
REFERENCES
Chapter 4 Verb Functions and Noun Objects
CHAPTER SUMMARY
4.1 POSITIVE AND NEGATIVE SOCIAL FORCES
4.1.1 Forces in Society and Operations on Objects
4.1.2 Assistive, Neutral and Resistive Objects
4.2 FRAMEWORK OF KNOWLEDGE
4.2.1 Hyper-dimensionality of Knowledge
4.2.2 Intertwined Spaces of Knowledge
4.2.3 Contours of Knowledge
4.2.4 Funicular Polygon of Concepts
4.3 COMPILATION OF KNOWLEDGE
4.3.1 Lexical Analysis for Knowledge
4.3.2 Parsing BOKS
4.3.3 Syntactic Analysis of Knowledge
4.3.4 Semantic Analysis for Knowledge
4.3.5 Knowledge Machine Code
4.4 DERIVATION OF KNOWLEDGE
4.4.1 Microscopic or Basic Assembly Level Knowledge BALK Instructions
4.4.2 Application Level (Knowledge) Programs ALKP
4.4.3 Universal Level (Knowledge) Programs ULKP
4.5 KNOWLEDGE MACHINE SOFTWARE HIERARCHY
4.6 KNOWLEDGE HARDWARE AND SOFTWARE SYSTEMS
4.7 CLASSICAL MIGRATION PATH OF KNOWLEDGE
4.7.1 Knowledge Traps
4.7.2 Transition at Generic Nodes
4.8 CONCLUSIONS
4.7 REFERENCES
Chapter 5 Humanistic and Semi-Human Systems

CHAPTER SUMMARY
5.1 Humanistic Chipsets
5.2 ESSENCE OF HUMAN ACTIVITY
5.2.1 Varieties of Noun Objects (NOs)
5.2.2 Types of Verb Function Commands (VFs)
5.3 SMART VERBS AND INTELLIGENT NOUNS
5.5.1 A Qualitative Synopsis of the Response
5.5.2 Non-linear Response
5.5.3 An Intelligent Response
5.5.4 Algorithmic Representation
5.5 EFFECTS OF INTELLIGENT RESPONSE
5.6 GRADATION OF KPU RESPONSES
5.6.1 Traditional Computer Response
5.6.2 Life Form Response
5.6.3 Rational Response
5.6.4 AI Response
5.6.5 Humanistic Response
5.6.6 Human Response
5.6.7 Other Types of Responses
5.7 FRAGMENTS OF OVERALL HUMAN ACTIVITY
5.7.1 Minor Tasks and Micro-codes
5.7.2 Major Ordeals and Complex Programs
5.7.3 The Microcode of the Humanistic Chip Set
5.8 DUAL KPU HUMAN INTERACTION MODEL
5.8.1 Bilateral Human Relations
5.8.2 Models of Human Interaction
5.9 REFERENCES
APPENDIX A: HUMAN INTERACTIONS
A.1 NONLINEAR RESPONSES
A.1.1 Exponential Representation
A.1.2 Memory effects
A.1.3 Saturation
A.1.4 Peaky response
A.1.5 Hysteresis effects
A.2 OSCILLATORY RESPONSE OF INTELLIGENT OBJECTS
APPENDIX B: KNOWLEDGE MACHINES FOR HUMAN INTERACTIONS
B.1 KM FOR HUMAN INTERACTIVE PROCESSES
Reference Interpersonal Relationships
B.2 KM FOR LABOR MANAGEMENT (LM) NEGOTIATION
B.2.1 Background of LM Negotiations
B.2.2 Constituents of Model for LM Negotiations
B.2.3 Demand Intensities of Labor and Management
B.2.4 Structure of the Model for LM Negotiations
B.2.5 Negotiation Process and Validation
B.2.6 Successful Negotiation
B.2.7 Impasse in LM Negotiations
B.2.8 Conclusions for LM Negotiation
Reference for LM Relationships (B.2)
B.3 KM FOR CORPORATE INTERACTIONS
B.3.1 Background of Economics Based Interactions
B.3.2 Expert System Concepts
B.3.3 Computational Aspects in Negotiations
B.3.4 Mathematical Representations for the Cost of Agreement (COA), Disagreement (COD), and Demand Intensity (DI)
B.3.5 Systems Model of Interaction
B.3.7 Conclusions for Corporate Negotiations
References for Corporate Negotiations
Chapter 6 Information and Knowledge Filters
CHAPTER SUMMARY
6.1 JUNK INFORMATION AND HYPE KNOWLEDGE
6.2 DESIGN OF CONVENTIONAL SIGNAL FILTERS
6.2.1 Types of Traditional Signal Filters
6.2.2 Active Filters
6.2.3 Digital Filters
6.3 SIGNAL WAVES AND KNOWLEDGE FLOW
6.4 THE (I «» K) FILTERS
6.4.1 Symbols as Objects And Functions
6.4.2 Role Of Humans
6.4.3 Precise Solutions And Confident Results
6.5 THE DESIGN OF (I «» K) FILTERS
6.5.1 Knowledge Filter Concepts
6.5.2 Noun Objects and Verb Functions
6.5.3 Scanning For Operative Noun and Verbs
6.6 CONFIGURATION OF (I «» K) SYSTEMS
6.6.1 Application Constraints
6.6.2 Design Concepts For (I «» K) Systems
6.6.3 Application For Filtering And Comparing
6.6.4 Low Pass and High Pass Information Filters
6.6.5 Design Steps For (I «» K) Filters
6.6.6 Design Methodology
6.7 SELECTION OF NOs AND VFs IN SAMPLES
6.8 SYSTEMS FOR (I «» K) FILTERS
6.9 TWO-PORT KNOWLEDGE NETWORKS
6.9.1 A Two Port Electrical Network
6.9.2 Configuration of a Two Port Knowledge Network
6.9.3 Mathematical Implications of the Two Port Network
6.9.3 Dimensionality of the Nine variables, A-I
6.9.4 Change of Operators (+, ×, / and =)
6.9.5 Intelligent Knowledge Two Port Networks
6.9.6 Needs, Knowledge, and Innovations
6.10 KNOWLEDGE GATES
6.10.1 KAND Knowledge Based AND Gate
6.10.2 KOR - Knowledge Based OR Gate
6.10.3 KNOT - Knowledge Based NOT Gate
6.10.4 Practical Use of Knowledge Gates
6.11 CONTAMINATION OF (I «» K)
6.12 DECONTAMINATION OF KNOWLEDGE
6.13 CONCLUSIONS
REFERENCES

APPENDIX-6.A: A TWO-STAGE ‘TR’ FILTER (HENRY HIGGINS)
6.A.1 T-Zero Filtering And Output BOK1-T
6.A.2 R-Zero Filtering And Output BOK1-R
6.A.3 TR-Zero Filtering And Output BOK2-TR
APPENDIX- 6.B: A THREE-STAGE ‘SET’ FILTER (JOHN TYNDALL)
6.B.1 S-Zero Filtering And Output BOK1-S
6.B.2 Generality of Information Filtering
APPENDIX-6.C: A PRACTICAL INFORMATION FILTER (PLATO AND EINSTEIN)
6.C.1 Application to Three Positive Noun Objects
6.C.2 Filter Template Based on TVB
6.C.3 New Filter Template Based on TVB and Soul
6.D APPLICATION TO THREE NEGATIVE NOUN OBJECTS
CHAPTER 7PROCESS AND CHANGE OF ENTROPY
CHAPTER SUMMARY
7.1 ACTIONS AND ENTROPY
7.2 KNOWLEDGE CENTRIC OBJECTS (KCO)
7.2.1 Passive Objects (KCOs)
7.2.2 Reactive or Intelligent Objects (KCOs)
7.3 CLASSIFICATION OF KCOs
7.3.1 Single Simple Knowledge Object (SSKO)
7.3.2 Single Simple Objects with Single Attribute (SSKO-SA)
7.3.3 Single Simple Object with Multiple Attributes (1- n)
7.3.4 Single Complex Objects with Single Dependent Object
7.3.5 Single Complex Object, Single Dependent Object, Single Attribute
7.3.6 Single Complex Object, Single Dependent Object, Multiple Attributes
7.3.7 Single Complex Object, Multiple Dependent Objects (ℓ)
7.3.8 Single Complex Object, Multiple Dependent Objects (ℓ), One Attribute
7.3.9 Single Complex Object, Multiple Dependent Objects (ℓ), Multiple Attributes (n)
7.4 Clusters of Complex KCOs
7.4.1 Multiple Complex Objects (m), Multiple Dependent Objects (ℓ), with Single Attribute
7.4.2 Multiple Complex Objects (m), Multiple Dependent Objects (ℓ), with Multiple Attributes (n)
7.5 Single Process Kopcodes for Generic KCOs
7.5.1 Single Process Kopcodes for Simple Objects
7.5.2 Single Process kopc for Single Complex Objects
7.5.3 Single Process kopc for Multiple Complex Objects
7.6 MULTIPLE PROCESS INSTRUCTIONS
7.6.1 MP-MCKO-MDO-NA, Class-16 kopc16 Instruction
7.6.2 MP-MCKO-MDO-SA, Class-17 kopc17 Instruction
7.6.3 MP-MCKO-MDO-MA, Class-18 kopc18 Instruction
7.7 PASSIVE KOPCS
7.7.1 Report Generation KOPCS on Passive KCOs
7.7.2 Report Generation KOPCS on Dynamic KCOs
7.8 ACTIVE KOPCS
7.8.1 Active kopcs for Passive KCOs
7.8.2 Active kopcs for Reactive KCOs
7.8.3 Active kopcs for Intelligent KCOs
7.9 MULTIPLE PROCESS INSTRUCTIONS
7.10 ITERATIVE AND REFLEXIVE PROCESSING
7.11 MACRO INSTRUCTIONS FOR KPU
7.12 KPU Architectures for KOPC01-12 Instructions
7.12.1 SPSO Processors and Machines
7.12.2 MPMO Processors and Machines
7.13 CONCLUSIONS
REFERENCES
CHAPTER 8KNOWLEDGE SYSTEM ARCHITECTURES
CHAPTER SUMMARY
8.1 FROM CPU TO KPU
8.2 THE PHILOSOPHIC DIMENSION
8.3 ITERATIVE CYCLIC SOCIAL PROCESSES
8.3.1 Awareness and Knowledge
8.3.2 Communications and Interactions
8.3.3 Bargaining and Negotiation
8.3.4 Compromise during Transactions
8.3.5 Adjustment and Relationships
8.4 THE SCIENTIFIC DIMENSION
8.4.1 The Search for Precision and Infallibility
8.4.2 Machine Accuracy and Human Adaptability
8.5 VARIETIES OF PROCESSORS AND MACHINES
8.5.1 Central Processor Units and Generic Computers
8.5.2 Communication Processor and ESS
8.5.3 Input/Output Processors (IOPs)
8.5.4 Display/Graphics Processor Units (DPUs/GPUs)
8.5.5 Numeric Processor Units and Array Processors
8.5.6 Digital Signal Processors
8.5.7 Digital Object Processing Environments
8.5.8 Digital Knowledge Environments
8.5.9 Digital Medical Processing Environments
8.6 THE TREND OF CONCEPTS
8.6.1 Bridge between Science and Wisdom
8.6.2 Concept Processing
8.6.3 Human-Concept Machines
8.7 RECENT TRENDS TOWARDS WISDOM
8.7.1 Artificial Wisdom
8.7.2 Old and New Wisdom
8.7.3 Wisdom in Machines and Instinct in Humans
8.8 THE TREND OF VALUES AND ETHICS
8.8.1 Ethical Issues and Role of Machines
8.8.2 Conflictive Roles of Humans and Machines
8.9 CONCLUSIONS
REFERENCES
CHAPTER 9HUMANS, MACHINES AND NETWORKS
CHAPTER SUMMARY
9.1 ETHICS AND VALUES IN HIGH-TECH SOCIETY
9.2 NEEDS THAT DRIVE
9.3 NETWORKS THAT TRANSPORT
9.4 OVERLAP OF NEEDS AND NETWORKS
9.4.1 The Human And Social Aspects
9.4.2 Individual Needs
9.4.3 Individuals, Machines And Networks
9.4.4 Corporate Needs
9.4.5 Corporations, Computers And Networks
9.4.6 Societal Needs
9.4.7 Societies, Machines and Networks
9.5 RATIONALITY OF HUMANISTIC MACHINES
9.5.1 The Human Element
9.5.2 The Open Human Interconnect (OHI) Model
9.5.2 Role of OHI in National Settings
9.6 WISDOM DOMAIN AND KNOWLEDGE RUSH
9.6.1 Pitfalls In Knowledge Society
9.6.2 Humanistic Systems that Refuse
9.7 NEED PYRAMID OF A SOCIETY
9.7.1 Individuals as Reputable Writers
9.7.2 Machines as Processors of Information
9.8 SELF PERPETUATING POWER LOOPS
9.9 CONVERGENCE OF K & M HIERARCHIES
9.9.1 The Hierarchy of Knowledge
9.9.2 Hierarchy of Motivation
9.10 KNOWLEDGE MACHINES ON KNOWLEDGE
9.11 CONCLUSIONS
REFERENCES
CHAPTER 10ARCHITECTURE OF KNOWLEDGE
CHAPTER SUMMARY
10.1 A NEW BREED OF KNOWLEDGE
10.2 THE KNOWLEDGE LOOP AND ITS STABILITY
10.3 CONTINUITY OF KNOWLEDGE
10.4 THREE ORIENTATIONS OF WISDOM
10.5 LONG-TERM MOVEMENTS WITHIN THE K-LOOP
10.6 CONFLICTIVE ROLES OF TVB‹›DAH ORIENTATIONS
10.7 TRACKING OF THE K-LOOPS
10.7.1 Expansionary Upward Movement (TVB)
10.7.2 Recessive Downward Movement (DAH)
10.8 DETAILS OF THE UPWARD MIGRATION
10.9 DETAILS OF THE DOWNWARD MIGRATION
10.10 KNOWLEDGE LOOPS IN X AND Y DIMENSIONS
10.11 FOUR PORTS OF SUPER NODE-K
10.12 CONSTRUCTION OF A KNOWLEDGE PLANE
10.12.1 Embedded NO’s and VF’s
10.12.2 Primary K-Plane in XY Dimensions
10.13 KNOWLEDGE BASES IN PRIMARY K-PLANE
10.14 SUCCESSIVE K-LOOPS IN T (TIME) DIMENSION
10.14.1 Stacking of K-Loops
10.14.2 Lessons from Knowledge Lost
10.14.3 Cosmic Space, Knowledge Space and Intellectual Space
10.15 THE NEBULA OF KNOWLEDGE (KNOWBULA)
10.16 HINDSIGHT AND FORESIGHT
10.16.1 Coarse Survey of Human Struggle
10.16.2 Scan of Modern Methodologies
10.16.3 Structured and Predictive Knowledge
10.17 KNOWLEDGE, FREEDOM AND CREATIVITY
10.17.1 Knowbula Almost Fills the Cube of Knowledge
10.17.2 Knowbula Loosely Fits the Cube of Knowledge
10.17.3 Knowbula Becomes Insignificant in Cube of Knowledge
10.18 KNOWLEDGE AND MONEY
10.19 PINNACLE OF MIND AND INFINITY OF THOUGHT
10.20 SOCIAL MIGRATION AND POLITICAL AGENDA
10.21 CONCLUSIONS