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Cybernetics

Cybernetics
Cybernetics is a transdisciplinary[1] approach for exploring regulatory systems, their structures, constraints, and possibilities. Cybernetics is relevant to the study of systems, such as mechanical, physical, biological, cognitive, and social systems. Cybernetics is applicable when a system being analyzed incorporates a closed signaling loop; that is, where action by the system generates some change in its environment and that change is reflected in that system in some manner (feedback) that triggers a system change, originally referred to as a "circular causal" relationship. Concepts studied by cyberneticists (or, as some prefer, cyberneticians) include, but are not limited to: learning, cognition, adaptation, social control, emergence, communication, efficiency, efficacy, and connectivity. Norbert Wiener defined cybernetics in 1948 as "the scientific study of control and communication in the animal and the machine Definitions[edit] Other notable definitions include: Etymology[edit] W.

Bionics Bionics (also known as bionical creativity engineering) is the application of biological methods and systems found in nature to the study and design of engineering systems and modern technology.[citation needed] The transfer of technology between lifeforms and manufactures is, according to proponents of bionic technology, desirable because evolutionary pressure typically forces living organisms, including fauna and flora, to become highly optimized and efficient. A classical example is the development of dirt- and water-repellent paint (coating) from the observation that the surface of the lotus flower plant is practically unsticky for anything (the lotus effect).[citation needed]. Ekso Bionics is currently developing and manufacturing intelligently powered exoskeleton bionic devices that can be strapped on as wearable robots to enhance the strength, mobility, and endurance of soldiers and paraplegics. The term "biomimetic" is preferred when reference is made to chemical reactions.

Information theory Overview[edit] The main concepts of information theory can be grasped by considering the most widespread means of human communication: language. Two important aspects of a concise language are as follows: First, the most common words (e.g., "a", "the", "I") should be shorter than less common words (e.g., "roundabout", "generation", "mediocre"), so that sentences will not be too long. Such a tradeoff in word length is analogous to data compression and is the essential aspect of source coding. Second, if part of a sentence is unheard or misheard due to noise — e.g., a passing car — the listener should still be able to glean the meaning of the underlying message. Note that these concerns have nothing to do with the importance of messages. Information theory is generally considered to have been founded in 1948 by Claude Shannon in his seminal work, "A Mathematical Theory of Communication". Historical background[edit] With it came the ideas of Quantities of information[edit] Entropy[edit] . that

Ecology and Ideology Return to Left Curve no. 21 Table of Contents by Peter Laska Thirty years ago the philosophy of ecology did not exist, ecology itself was a little known science; and the radical environmental movement, spurred by revelations in books like Rachel Carson's Silent Spring, was just getting under way. Today the literature on ecological topics is enormous and the theoretical work devoted to the ecological idea and its implications is large and growing. My reason for noting the last two works has todo with the fact that the concept of ecology as a science is missing from the above three anthologies. As a science, ecology studies the interrelationships of living things in their abiotic environments. Subsequent developments have proven this perception correct. The result is a kind of dream sequence or collec- tive hallucination in which dogmatic skepticism comes back into fashion as a way of maintaining one's grip. Under the control of market imperatives conformism is self-enforcing.

Robotics Robotics is the branch of mechanical engineering, electrical engineering and computer science that deals with the design, construction, operation, and application of robots,[1] as well as computer systems for their control, sensory feedback, and information processing. These technologies deal with automated machines that can take the place of humans in dangerous environments or manufacturing processes, or resemble humans in appearance, behavior, and/or cognition. Many of today's robots are inspired by nature contributing to the field of bio-inspired robotics. The concept of creating machines that can operate autonomously dates back to classical times, but research into the functionality and potential uses of robots did not grow substantially until the 20th century.[2] Throughout history, robotics has been often seen to mimic human behavior, and often manage tasks in a similar fashion. Etymology[edit] History of robotics[edit] Robotic aspects[edit] Components[edit] Power source[edit]

Decision theory Normative and descriptive decision theory[edit] Since people usually do not behave in ways consistent with axiomatic rules, often their own, leading to violations of optimality, there is a related area of study, called a positive or descriptive discipline, attempting to describe what people will actually do. Since the normative, optimal decision often creates hypotheses for testing against actual behaviour, the two fields are closely linked. Furthermore it is possible to relax the assumptions of perfect information, rationality and so forth in various ways, and produce a series of different prescriptions or predictions about behaviour, allowing for further tests of the kind of decision-making that occurs in practice. In recent decades, there has been increasing interest in what is sometimes called 'behavioral decision theory' and this has contributed to a re-evaluation of what rational decision-making requires.[1] What kinds of decisions need a theory? Choice under uncertainty[edit]

Différance Différance is a French term coined by Jacques Derrida, deliberately homophonous with the word "différence". Différance plays on the fact that the French word différer means both "to defer" and "to differ." Derrida first uses the term différance in his 1963 paper "Cogito et histoire de la folie".[1] The term différance then played a key role in Derrida's engagement with the philosophy of Edmund Husserl in Speech and Phenomena. The term was then elaborated in various other works, notably in his essay "Différance" and in various interviews collected in Positions.[2] The 〈a〉 of différance is a deliberate misspelling of différence, though the two are pronounced identically (IPA: [difeʁɑ̃s]). Différance – between structure and genesis[edit] Saussure is considered one of the fathers of structuralism when he explained that terms get their meaning in reciprocal determination with other terms inside language: In language there are only differences. Illustration of différance[edit]

Technological singularity The technological singularity is the hypothesis that accelerating progress in technologies will cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and control, thus radically changing civilization in an event called the singularity.[1] Because the capabilities of such an intelligence may be impossible for a human to comprehend, the technological singularity is an occurrence beyond which events may become unpredictable, unfavorable, or even unfathomable.[2] The first use of the term "singularity" in this context was by mathematician John von Neumann. Proponents of the singularity typically postulate an "intelligence explosion",[5][6] where superintelligences design successive generations of increasingly powerful minds, that might occur very quickly and might not stop until the agent's cognitive abilities greatly surpass that of any human. Basic concepts Superintelligence Non-AI singularity Intelligence explosion Exponential growth Plausibility

Cray-1 Cray-1 with internals exposed at EPFL The Cray-1 was a supercomputer designed, manufactured and marketed by Cray Research. The first Cray-1 system was installed at Los Alamos National Laboratory in 1976 and it went on to become one of the best known and most successful supercomputers in history. History[edit] Jim Thornton, formerly Cray's engineering partner on earlier designs, had started a more radical project known as the CDC STAR-100. As a result, Cray left CDC and started a new company HQ only yards from the CDC lab. In 1975 the 80 MHz Cray-1 was announced. The 80 MFLOPS Cray-1 was succeeded in 1982 by the 800 MFLOPS Cray X-MP, the first Cray multi-processing computer. Background[edit] Typical scientific workloads consist of reading in large data sets, transforming them in some way and then writing them back out again. Vector machines[edit] In the STAR, new instructions essentially wrote the loops for the user. The real savings are not so obvious. Cray's approach[edit] Cray-1S[edit]

Dasein Dasein (German pronunciation: [ˈdaːzaɪn]) is a German word which means "being there" or "presence" (German: da "there"; sein "being") often translated in English with the word "existence". It is a fundamental concept in the existential philosophy of Martin Heidegger particularly in his magnum opus Being and Time. Heidegger uses the expression Dasein to refer to the experience of being that is peculiar to human beings. Thus it is a form of being that is aware of and must confront such issues as personhood, mortality and the dilemma or paradox of living in relationship with other humans while being ultimately alone with oneself. Heidegger's re-interpretation[edit] In German, Dasein is the vernacular term for "existence", as in "I am pleased with my existence" (ich bin mit meinem Dasein zufrieden). Heidegger also saw the question of Dasein as extending beyond the realms disclosed by positive science or in the history of metaphysics. Origin and inspiration[edit] Other applications[edit]

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