scholarly journals Increasing Discovery in Research, Design, and Other Processes with Artificial General Intelligence and General Collective Intelligence

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
State Space ◽  
Research Design ◽  
Functional State ◽  
Collective Intelligence ◽  
Human Cognition ◽  
General Intelligence ◽  
Problem Domain ◽  
Minimal Set ◽  
Business Operations ◽  
Functional States

Any system with repeatable behavior can potentially be defined with the minimal set of functions that might be composed to represent the entirety of that behavior. The states accessible through these functions then forms a “functional state space” through which the system moves. Since functional states spaces can be used to represent every problem domain from physics, to communications, to business operations, to the human cognition itself, a general approach to not only research but design and all other processes of discovery that is applicable to all domains can potentially be defined to radically increase capacity for discovery in each domain.

scholarly journals General Collective Intelligence vs the Innate Collective Intelligence Factor

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
State Space ◽  
Functional State ◽  
General Problem ◽  
Collective Intelligence ◽  
Functional Modelling ◽  
Collective Cognition ◽  
Potential Capacity ◽  
Modelling Approach

INTRODUCTION: Groups of individuals of species exhibiting collective behaviours have been suggested to have some innate general collective intelligence. General Collective Intelligence or GCI has been described as a platform that organizes individual humans into a single collective intelligence with the potential capacity for exponentially greater general problem-solving ability.OBJECTIVES: To explore whether a functional modelling approach might have the capacity to represent any system of organization resulting in a general collective intelligence factor. And to explore what functionality might be required for a GCI to exponentially increase it.METHODS: An analysis of the meaning of general problem-solving ability in the functional state space of a system of cognition or collective cognition is used to assess whether GCI has the potential to exponentially increase increase that ability.RESULTS: GCI has the potential to exponentially increase increase impact on all general outcomes where limited by general problem-solving abilityCONCLUSION: While an innate general collective intelligence factor might exist, and while conventional CI solutions might have significant impact on specific collective outcomes, a GCI is required to exponentially general problem-solving ability, and therefore to exponentially increase collective outcomes. This capacity has the potential to be disruptive.

scholarly journals Individualization of Products and Services with Artificial General Intelligence and General Collective Intelligence

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Online Education ◽  
News Media ◽  
Intelligent Agents ◽  
Collective Intelligence ◽  
Online News ◽  
General Intelligence ◽  
Entertainment Media ◽  
Individual User ◽  
Artificial General Intelligence ◽  
The Individual

INTRODUCTION: With advances in big data techniques having already led to search results and advertising being customized to the individual user, the concept of an online education designed solely for an individual, or the concept of online news or entertainment media, or any other virtual service being designed uniquely for each individual, no longer seems as far fetched. However, designing services that maximize user outcomes as opposed to services that maximize outcomes for the corporation owning them, requires modeling user processes and the outcomes they target.OBJECTIVES: To explore the use of Human-Centric Functional Modeling (HCFM) to define functional state spaces within which human processes are well-defined paths, and within which products and services solve specific navigation problems, so that by considering all of any given individual’s desired paths through a given state space, it is possible to automate the customization of those products and services for that individual or to groups of individuals.METHODS: An analysis is performed to assess how and whether intelligent agents based on some subset of functionality required for Artificial General Intelligence (AGI) might be used to optimize for the individual user. And an analysis is performed to determine whether and if so how General Collective Intelligence (GCI) might be used to optimize across all users.RESULTS: AGI and GCI create the possibility to individualize products and services, even shared services such as the Internet, or news services so that every individual sees a different version.CONCLUSION: The conceptual example of customizing a news media website for two individual users of opposite political persuasions suggests that while the overhead of customizing such services might potentially result in massively increased storage and processing overhead, within a network of cooperating services in which this customization reliably creates value, this is potentially a significant opportunity.

On the Construction of Relativistic Representation Spaces in Functional Quantum Theory of the Nonlinear Spinor Field

1975 ◽  
Vol 30 (11) ◽  
pp. 1361-1371 ◽  
Author(s):  
H. Stumpf ◽  
K. Scheerer
Keyword(s):  
Quantum Theory ◽  
State Space ◽  
Functional State ◽  
Spinor Field ◽  
Function Spaces ◽  
The State ◽  
Nonlinear Spinor ◽  
Spinor Theory ◽  
State Spaces ◽  
Representation Spaces

Functional quantum theory is defined by an isomorphism of the state space H of a conventional quantum theory into an appropriate functional state space D It is a constructive approach to quantum theory in those cases where the state spaces H of physical eigenstates cannot be calculated explicitly like in nonlinear spinor field quantum theory. For the foundation of functional quantum theory appropriate functional state spaces have to be constructed which have to be representation spaces of the corresponding invariance groups. In this paper, this problem is treated for the spinor field. Using anticommuting source operator, it is shown that the construction problem of these spaces is tightly connected with the construction of appropriate relativistic function spaces. This is discussed in detail and explicit representations of the function spaces are given. Imposing no artificial restrictions it follows that the resulting functional spaces are indefinite. Physically the indefiniteness results from the inclusion of tachyon states. It is reasonable to assume a tight connection of these tachyon states with the ghost states introduced by Heisenberg for the regularization of the nonrenormalizable spinor theory

scholarly journals AI Safety and General Collective Intelligence

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Collective Intelligence ◽  
The Other ◽  
General Intelligence ◽  
Human Beings ◽  
Artificial General Intelligence ◽  
The Future ◽  
Ai Safety

Considering both current narrow AI, and any Artificial General Intelligence (AGI) that might be implemented in the future, there are two categories of ways such systems might be made safe for the human beings that interact with them. One category consists of mechanisms that are internal to the system, and the other category consists of mechanisms that are external to the system. In either case, the complexity of the behaviours that such systems might be capable of can rise to the point at which such measures cannot be reliably implemented. However, General Collective Intelligence or GCI can exponentially increase the general problem-solving ability of groups, and therefore their ability to manage complexity. This paper explores the specific cases in which AI or AGI safety cannot be reliably assured without GCI.

scholarly journals Cognitive Computing and its Relationship to Computing Methods and Advanced Computing from a Functional Modeling Perspective

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Collective Intelligence ◽  
Computing Methods ◽  
Modeling Technique ◽  
Human Cognition ◽  
Cognitive Computing ◽  
Functional Modeling ◽  
Semantic Modeling ◽  
Advanced Computing

Recent advances in modeling human cognition have resulted in what is suggested to be the first model of Artificial General Intelligence (AGI) with the potential capacity for human-like general problem-solving ability, as well as a model for a General Collective Intelligence or GCI, which has been described as software that organizes a group into a single collective intelligence with the potential for vastly greater general problem-solving ability than any individual in the group. Both this model for GCI and this model for AGI require functional modeling of concepts that is complete in terms of meaning being self-contained in the model and not requiring interpretation based on information outside the model. This definition of a model for cognition has also been suggested to implicitly provide a semantic interpretation of functional models created within the functional modeling technique defined to meet the data format requirements of this AGI and GCI, so that the combination of the model of cognition to define an interpretation of meaning, and the functional modeling technique, together result in fully self-contained definitions of meaning that are suggested to be the first complete implementation of semantic modeling. With this semantic modeling, and with these models for AGI and GCI, cognitive computing is far better defined. This paper explores the various computing methods and advanced computing paradigms from the perspective of this cognitive computing.

scholarly journals Patterns of neurodegeneration in dementia reflect a global functional state space

2020 ◽  
Author(s):  
D. Jones ◽  
V. Lowe ◽  
J. Graff-Radford ◽  
H. Botha ◽  
D. Wiepert ◽  
...  
Keyword(s):  
Information Processing ◽  
State Space ◽  
Functional State ◽  
Large Scale ◽  
Clinical Symptoms ◽  
Brain Regions ◽  
Clinical Neurology ◽  
Brain Anatomy ◽  
Mental Functions ◽  
Mental Abilities

AbstractDisruption of mental functions in Alzheimer’s disease (AD) and related disorders is accompanied by selective degeneration of brain regions for unknown reasons. These regions comprise large-scale ensembles of cells organized into networks required for mental functioning. A mechanistic framework does not exist to explain the relationship between clinical symptoms of dementia, patterns of neurodegeneration, and the functional connectome. The association between dementia symptoms and degenerative brain anatomy encodes a mapping between mental functions and neuroanatomy. We isolated this mapping through unsupervised decoding of neurodegeneration in humans. This reflected a simple information processing-based functional description of macroscale brain anatomy, the global functional state space (GFSS). We then linked the GFSS to AD physiology, functional networks, and mental abilities. We extended the GFSS framework to normal aging and seven degenerative diseases of mental functions.One Sentence SummaryA global information processing framework for mental functions links neuroanatomy, cognitive neuroscience and clinical neurology.

scholarly journals Analysis of current research in the field of detecting driver fatigue in the vehicle cab

2021 ◽  
pp. 19-36
Author(s):  
Alexandr O. Bulygin ◽  
◽  
Alexey M. Kashevnik ◽  
Keyword(s):  
Functional State ◽  
Continuous Monitoring ◽  
Dynamic Assessment ◽  
Driver Behavior ◽  
Neurophysiological Monitoring ◽  
Time Interval ◽  
Driver Fatigue ◽  
Work Training ◽  
Functional States ◽  
Impaired Attention

The article analyzes the methods of detecting driver fatigue which are described in modern literature. There are a great variety of methods for assessing the functional state of a person. A functional state is an integral set of characteristics of those functions and qualities of a person that directly or indirectly determine the performance of any activity. The physical and mental state of a person, the success of his work, training, creativity depends on the functional state of the organism. The assessment of dynamic driver behavior has become an increasingly popular area of research in recent years. Dynamic assessment of driver behavior includes continuous monitoring that allows you to determine functional states, in contrast to modern driver monitoring systems, which assess conditions such as drowsiness and impaired attention for a short (1-10 s) time interval. Such systems allow us to talk about physiological, but not neurophysiological monitoring, which allows monitoring the functional state of fatigue. Therefore, it makes sense to monitor the driver’s state of fatigue of, as well as to warn them in a timely manner to avoid collisions with other vehicles. In the article, a study was carried out and an analysis of the ways to obtain the appropriate characteristics from a person, with the help of which it is possible to determine his functional state of fatigue. As a result of the analysis of the sources, the most common methods for determining the functional state of the driver were selected. Further, the sources found were classified according to the most common methods for obtaining significant characteristics of the functional state of the driver. As a result, a comparative analysis was made, demonstrating the capabilities of modern systems of this class.

A Strategy and Architecture for the Visualization of Complex Geographical Datasets

1997 ◽  
Vol 11 (02) ◽  
pp. 239-261 ◽  
Author(s):  
Mark Gahegan ◽  
David O'Brien
Keyword(s):  
Exploratory Data Analysis ◽  
Mineral Exploration ◽  
Environmental Data ◽  
Human Cognition ◽  
Problem Domain ◽  
Visual Attributes ◽  
Computer Visualization ◽  
Geographic Datasets ◽  
Exploratory Data ◽  
Use Of Knowledge

The use of computer visualization as a means to analyze complex geographic datasets is discussed. Visualization is a valuable tool for conducting exploratory data analysis on geographical data; making good use of the human eye's unparalleled ability to recognize structure and relationships that may be inherent within the data. Traditional GIS are extremely poor at visualization, being limited to a very restricted set of visual attributes with which to convey information (position, size, color). The use of a more sophisticated approach is discussed in detail. Specifically, a system to visualise complex environmental datasets is described, which makes use of knowledge concerning the problem domain as well as knowledge concerning human cognition. In the realizations produced, the most salient attributes in the data, for a particular task, are assigned to the most striking visual attributes. Assignments are controlled by heuristics that may be changed to alter system behavior. Results are presented showing the application of this approach on datasets involving several multi-dimensional thematic layers of environmental data, used in mineral exploration.

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