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Intelligence amplification

Intelligence amplification
Intelligence amplification (IA) (also referred to as cognitive augmentation and machine augmented intelligence) refers to the effective use of information technology in augmenting human intelligence. The idea was first proposed in the 1950s and 1960s by cybernetics and early computer pioneers. IA is sometimes contrasted with AI (Artificial Intelligence), that is, the project of building a human-like intelligence in the form of an autonomous technological system such as a computer or robot. AI has encountered many fundamental obstacles, practical as well as theoretical, which for IA seem moot, as it needs technology merely as an extra support for an autonomous intelligence that has already proven to function. Major contributions[edit] William Ross Ashby: Intelligence Amplification[edit] .." J. "Man-Computer Symbiosis" is a key speculative paper published in 1960 by psychologist/computer scientist J.C.R. Man-computer symbiosis is a subclass of man-machine systems. See also[edit] Related:  Intelligence FormsBrain Augmentation

Cattell–Horn–Carroll theory The Cattell–Horn–Carroll theory, or CHC theory, is a psychological theory of human cognitive abilities that takes its name from Raymond Cattell, John L. Horn and John Bissell Carroll. Recent advances in current theory and research on the structure of human cognitive abilities have resulted in a new empirically derived model commonly referred to as the Cattell–Horn–Carroll theory of cognitive abilities. CHC theory of cognitive abilities is an amalgamation of two similar theories about the content and structure of human cognitive abilities. Abilities[edit] There are 9 broad stratum abilities and over 70 narrow abilities below these. A tenth ability, Gt, is considered part of the theory, but is not currently assessed by any major intellectual ability test. McGrew proposes a number of extensions to CHC theory, including Gkn, Domain-specific knowledge, Gp, Psychomotor ability, and Gps, Psychomotor speed. Model tests[edit] See also[edit] Fluid and crystallized intelligence for Gf-Gc theory

Nootropic Nootropics (/noʊ.əˈtrɒpɨks/ noh-ə-TROP-iks), also referred to as smart drugs, memory enhancers, neuro enhancers, cognitive enhancers, and intelligence enhancers, are drugs, supplements, nutraceuticals, and functional foods that improve one or more aspects of mental function, such as working memory, motivation, and attention.[1][2] The word nootropic was coined in 1972 by the Romanian Dr. Corneliu E. Giurgea,[3][4] derived from the Greek words νους nous, or "mind", and τρέπειν trepein meaning to bend or turn.[5] Availability and prevalence[edit] At present, there are only a few drugs which have been shown to improve some aspect of cognition in medical reviews. These drugs are purportedly used primarily to treat cognitive or motor function difficulties attributable to such disorders as Alzheimer's disease, Parkinson's disease, Huntington's disease and ADHD. Academic use[edit] Several factors positively and negatively influence the use of drugs to increase cognitive performance. Drugs[edit]

Artificial intelligence AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other.[5] Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.[6] General intelligence is still among the field's long-term goals.[7] Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—"can be so precisely described that a machine can be made to simulate it History[edit]

Three stratum theory Presented by John Carroll 1993 in "Human cognitive abilities: A survey of factor-analytic studies",[1][2] the hierarchical Three-Stratum Theory of cognitive abilities is based on a factor analytic study of correlation of individual differences variables from measures including psychological tests, school marks, and competence ratings. These factor analyses suggested three layers or strata, with each layer accounting for the variation in correlations among elements at the next lower level. Carroll proposes a taxonomic dimension in the distinction between level factors and speed factors. The tasks that contribute to the identification of level factors can be sorted by difficulty and individuals differentiated by whether they have acquired the skill to perform the tasks. Tasks that contribute to speed factors are distinguished by the relative speed with which individuals can complete them. References[edit] Jump up ^ J. See also[edit]

Cyberware Cyberware is a relatively new and unknown field (a proto-science, or more adequately a “proto-technology”). In science fiction circles, however, it is commonly known to mean the hardware or machine parts implanted in the human body and acting as an interface between the central nervous system and the computers or machinery connected to it. More formally: Cyberware is technology that attempts to create a working interface between machines/computers and the human nervous system, including (but not limited to) the brain. Examples of potential cyberware cover a wide range, but current research tends to approach the field from one of two different angles: Interfaces or Prosthetics. Interfaces ("Headware")[edit] Large university laboratories conduct most of the experiments done in the area of direct neural interfaces. The more intense research, concerning full in-brain interfaces, is being studied, but is in its infancy. Prosthetics ("Bodyware")[edit] See also[edit] References[edit]

Encapsulation (object-oriented programming) In programming languages, encapsulation is used to refer to one of two related but distinct notions, and sometimes to the combination[1][2] thereof: The second definition is motivated by the fact that in many OOP languages hiding of components is not automatic or can be overridden; thus, information hiding is defined as a separate notion by those who prefer the second definition. class Program { public class Account { private decimal accountBalance = 500.00m; public decimal CheckBalance() { return accountBalance; } } static void Main() { Account myAccount = new Account(); decimal myBalance = myAccount.CheckBalance(); /* This Main method can check the balance via the public * "CheckBalance" method provided by the "Account" class * but it cannot manipulate the value of "accountBalance" */ }} Below is an example in Java: Encapsulation is also possible in older, non-object-oriented languages. Clients call the API functions to allocate, operate on, and deallocate objects of an opaque type.

Convergent and divergent production Convergent and divergent production are the two types of human response to a set problem that were identified by J.P. Guilford (1967). Guilford observed that most individuals display a preference for either convergent or divergent thinking. Others observe that most people prefer a convergent closure. Divergent thinking[edit] According to J.P. There is a movement in education that maintains divergent thinking might create more resourceful students. Divergent production is the creative generation of multiple answers to a set problem. Critic of the analytic/dialectic approach[edit] While the observations made in psychology can be used to analyze the thinking of humans, such categories may also lead to oversimplifications and dialectic thinking. The systematic use of convergent thinking may well lead to what is known as Group think—thus one should probably combine systematic use with critical thinking. References[edit] Guilford, J. (1967). See also[edit]

Exocortex An exocortex is a theoretical artificial external information processing system that would augment a brain's biological high-level cognitive processes. An individual's exocortex would be composed of external memory modules, processors, IO devices and software systems that would interact with, and augment, a person's biological brain. Typically this interaction is described as being conducted through a direct brain-computer interface, making these extensions functionally part of the individual's mind. Individuals with significant exocortices could be classified as cyborgs or transhumans. Living Digital provided one description of the concept: While [the traditional concept of] a cyborg has included artificial mechanical limbs, embedded chips and devices, another interesting concept is the exocortex, which is a brain-computer interface. Etymology[edit] Specific applications[edit] In 1981 Steve Mann designed and built the first general purpose wearable computer. Intellectual background[edit]

Object-oriented design Object-oriented design is the process of planning a system of interacting objects for the purpose of solving a software problem. It is one approach to software design. Overview[edit] What follows is a description of the class-based subset of object-oriented design, which does not include object prototype-based approaches where objects are not typically obtained by instancing classes but by cloning other (prototype) objects. Object-oriented design topics[edit] Input (sources) for object-oriented design[edit] The input for object-oriented design is provided by the output of object-oriented analysis. Some typical input artifacts for object-oriented design are: Object-oriented concepts[edit] The five basic concepts of object-oriented design are the implementation level features that are built into the programming language. Designing concepts[edit] Output (deliverables) of object-oriented design[edit] Some design principles and strategies[edit] See also[edit] References[edit] External links[edit]

Triarchic theory of intelligence Different components of information processing[edit] Schematic illustrating one trial of each stimulus pool in the Sternberg task: letter, word, object, spatial, grating. Sternberg associated the workings of the mind with a series of components. These components he labeled the metacomponents, performance components, and knowledge-acquisition components (Sternberg, 1985). The metacomponents are executive processes used in problem solving and decision making that involve the majority of managing our mind. Sternberg’s next set of components, performance components, are the processes that actually carry out the actions the metacomponents dictate. The last set of components, knowledge-acquisition components, are used in obtaining new information. Whereas Sternberg explains that the basic information processing components underlying the three parts of his triarchic theory are the same, different contexts and different tasks require different kind of intelligence (Sternberg, 2001). See also[edit]

First-Ever Incredible Footage of a Thought Being Formed Abstraction (computer science) Abstraction captures only those details about an object that are relevant to the current perspective; in both computing and in mathematics, numbers are concepts in programming languages. Numbers can be represented in myriad ways in hardware and software, but, irrespective of how this is done, numerical operations will obey identical rules. Abstraction can apply to control or to data: Control abstraction is the abstraction of actions while data abstraction is that of data structures. Control abstraction involves the use of subprograms and related concepts control flowsData abstraction allows handling data bits in meaningful ways. Computing mostly operates independently of the concrete world: The hardware implements a model of computation that is interchangeable with others. A central form of abstraction in computing is language abstraction: new artificial languages are developed to express specific aspects of a system. a := (1 + 2) * 5

PASS theory of intelligence Description[edit] Based on A. R. Luria’s (1966) seminal work on the modularization of brain function, and supported by decades of neuroimaging research, the PASS Theory of Intelligence[2] proposes that cognition is organized in three systems and four processes. The first is the Planning, which involves executive functions responsible for controlling and organizing behavior, selecting and constructing strategies, and monitoring performance. The second is the Attention process, which is responsible for maintaining arousal levels and alertness, and ensuring focus on relevant stimuli. Assessment of PASS processes[edit] The PASS theory provides the theoretical framework for a measurement instrument called the Das-Naglieri Cognitive Assessment System (CAS), published in 1997.[5] This test is designed to provide a nuanced assessment of the individual’s intellectual functioning, providing information about cognitive strengths and weaknesses in each of the four processes. Challenges[edit] Das, J.

Sensor chip for implanting into a brain

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