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Moore's law

Moore's law
Moore's law is the observation that, over the history of computing hardware, the number of transistors on integrated circuits doubles approximately every two years. The law is named after Intel co-founder Gordon E. Moore, who described the trend in his 1965 paper.[1][2][3] His prediction has proven to be accurate, in part because the law is now used in the semiconductor industry to guide long-term planning and to set targets for research and development.[4] The capabilities of many digital electronic devices are strongly linked to Moore's law: processing speed, memory capacity, sensors and even the number and size of pixels in digital cameras.[5] All of these are improving at roughly exponential rates as well. The period is often quoted as 18 months because of Intel executive David House, who predicted that chip performance would double every 18 months (being a combination of the effect of more transistors and their being faster).[9] History[edit] Gordon Moore in 2004 Network capacity. Related:  The Singularity

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

Chaos theory A double rod pendulum animation showing chaotic behavior. Starting the pendulum from a slightly different initial condition would result in a completely different trajectory. The double rod pendulum is one of the simplest dynamical systems that has chaotic solutions. Chaos: When the present determines the future, but the approximate present does not approximately determine the future. Chaotic behavior can be observed in many natural systems, such as weather and climate.[6][7] This behavior can be studied through analysis of a chaotic mathematical model, or through analytical techniques such as recurrence plots and Poincaré maps. Introduction[edit] Chaos theory concerns deterministic systems whose behavior can in principle be predicted. Chaotic dynamics[edit] The map defined by x → 4 x (1 – x) and y → x + y mod 1 displays sensitivity to initial conditions. In common usage, "chaos" means "a state of disorder".[9] However, in chaos theory, the term is defined more precisely. where , and , is: .

Moore's Law A Cosmist Manifesto Emerging Memetic Singularity in the Global Knowledge Society 30 April 2009 | Draft IntroductionChecklist of constraintsVarieties of singularity -- Technological singularity | Cognitive singularity | Metasystem transition -- Communication singularity | Globality as singularity | Symmetry group singularity -- Subjective singularity | Spiritual singularity | Singularity of planetary consciousness -- Metaphorical singularityEnd times scenarios -- End of history | 2012 | Timewave theory | Eschatological scenarios | End of science -- End of culture | End of religion | End of civilization | End of security | End of privacy -- End of intelligence | End of ignorance | End of knowing | End of abundance | End of confidence -- End of hope | End of truth | End of faith | End of logic | End of rationality | End of modernism -- End of wisdom | End of tolerance | End of natureBlack holes and Event horizonsConclusion Introduction Historically these were a preoccupation of the Union of Intelligible Associations and are now a focus of Global Sensemaking.

Moore's Law 2 Butterfly effect In chaos theory, the butterfly effect is the sensitive dependency on initial conditions in which a small change at one place in a deterministic nonlinear system can result in large differences in a later state. The name of the effect, coined by Edward Lorenz, is derived from the theoretical example of a hurricane's formation being contingent on whether or not a distant butterfly had flapped its wings several weeks earlier. Although the butterfly effect may appear to be an unlikely behavior, it is exhibited by very simple systems. For example, a ball placed at the crest of a hill may roll into any surrounding valley depending on, among other things, slight differences in its initial position. History[edit] Chaos theory and the sensitive dependence on initial conditions was described in the literature in a particular case of the three-body problem by Henri Poincaré in 1890.[1] He later proposed that such phenomena could be common, for example, in meteorology. Illustration[edit] , then

Institute for Ethics and Emerging Technologies The Law of Accelerating Returns Autopoiesis 3D representation of a living cell during the process of mitosis, example of an autopoietic system. The original definition can be found in Autopoiesis and Cognition: the Realization of the Living (1st edition 1973, 2nd 1980): Page 78: - An autopoietic machine is a machine organized (defined as a unity) as a network of processes of production (transformation and destruction) of components which: (i) through their interactions and transformations continuously regenerate and realize the network of processes (relations) that produced them; and (ii) constitute it (the machine) as a concrete unity in space in which they (the components) exist by specifying the topological domain of its realization as such a network. [1] Page 89:- [...] the space defined by an autopoietic system is self-contained and cannot be described by using dimensions that define another space. Meaning[edit] Criticism[edit] See also[edit] Notes and references[edit] Further reading[edit] External links[edit]

The Emergence of Collective Intelligence | Ledface Blog ~Aristotle When we observe large schools of fish swimming, we might wonder who is choreographing that complex and sophisticated dance, in which thousands of individuals move in harmony as if they knew exactly what to do to produce the collective spectacle. So, what is “Emergence”? School of fishes dancing is an example of “emergence”, a process where new properties, behaviors, or complex patterns results of relatively simple rules and interactions. One can see emergence as some magic phenomena or just as a surprising result caused by the current inability of our reductionist mind to understand complex patterns. Whichever way we think, examples of emerging behaviors are abundant in nature, science, and society and are are just a fact of life. Humans can do it too We humans have even built artificial environments that allow for collective intelligence to express itself. Each and every actor in the financial markets has no significant control over or awareness of its inputs.

Kurzweil's: "The Law of Accelerating Returns": Self-organization Self-organization occurs in a variety of physical, chemical, biological, robotic, social and cognitive systems. Common examples include crystallization, the emergence of convection patterns in a liquid heated from below, chemical oscillators, swarming in groups of animals, and the way neural networks learn to recognize complex patterns. Overview[edit] The most robust and unambiguous examples[1] of self-organizing systems are from the physics of non-equilibrium processes. Sometimes the notion of self-organization is conflated with that of the related concept of emergence, because "[t]he order from chaos, presented by Self-Organizing models, is often interpreted in terms of emergence".[2] Properly defined, however, there may be instances of self-organization without emergence and emergence without self-organization, and it is clear from the literature that the phenomena are not the same. Self-organization usually relies on three basic ingredients:[3] Principles of self-organization[edit]

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