“Neural Computing is the study of networks of adaptable nodes which through a process of learning from task examples, store experiential knowledge and make it available for use.”

Source: An introduction to neural computing (1990), p.1

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Igor Aleksander9

scientist 1937

Igor Aleksander (1937) scientist

As cited in: Brian D. Ripley (2008) Pattern Recognition and Neural Networks. p.4
An introduction to neural computing (1990)

“Neural computing is the study of cellular networks that have a natural property for storing experimental knowledge. Such systems bear a resemblance to the brain in the sense that knowledge is acquired through training rather than programming and is retained due to changes in node functions. The knowledge takes the form of stable states or cycles of states in the operation of the et. A central property of such nets is to recall these states or cycles in response to the presentation of cues.”

Igor Aleksander (1937) scientist

Aleksander & Morton (1989) Neural computing architectures: the design of brain-like machines. p.2 as cited in: M.A. Lovell et al. (1997) Developments in petrophysics. p.169

“The main theme of this report is a particular facet of the general problem of pre-organization in self-organizing systems, namely, the theory and circuitry of information processing networks. One may consider these networks as a special type of parallel computation channels which extract from the set of all possible inputs a particular subset which is deﬁned by the internal structure of the network. The advantage of such operationally deterministic networks in connection with adaptive systems is the obvious reduction in channel capacity of the adaptors, if it is possible to predetermine classes of inputs which are supposed to be meaningful for those interacting with the automaton”

Heinz von Foerster (1911–2002) Austrian American scientist and cybernetician

Von Foerster (1963, p. ii) as cited in Peter M. Asaro (2007). "Heinz von Foerster and the Bio-Computing Movements of the 1960s," http://cybersophe.org/writing/Asaro%20HVF%26BCL.pdf <br class="br">1960s

“To achieve this, we have to distinctively promote continuing and lifelong education, the form of education which is responsive to individual needs and preferences. With educational facilities and a variety of educational programs available, people can make use of the learning centre as a place to acquire technical skills or knowledge adaptive to their work and daily life activities.”

Sukavich Rangsitpol (1935) Thai politician

http://unesdoc.unesco.org/images/0012/001221/122102Eo.pdf Page53-56
Education for All People and Education for Life

“the mind is a neural computer”

Steven Pinker book How the Mind Works

Source: How the Mind Works

“There is a multilayering of global networks in the key strategic activities that structure and destructure the planet. When these multilayered networks overlap in some node, when there is a node that belongs to different networks, two major consequences follow. First, economies of synergy between these different networks take place in that node: between financial markets and media businesses; or between academic research and technology development and innovation; between politics and media.”

Manuel Castells (1942) Spanish sociologist (b.1942)

The Rise of the Network Society, 1996

“The fact that a computer player wins a game of chess or bridge with a human does not necessarily mean that the device is intelligent. The victory results from the fact that in the final analysis the device has been applied appropriate algorithms developed by man, e. g. using the properties of artificial neural networks. It is not the device that wins with a man, e. g. a chess player, but a man – the designer of the device. It is simply the rivalry of one intellect with another through the medium of computer science.”

Zygmunt Vetulani (1950) Polish mathematician

Tumiłowicz, Bronisław (February 2018): Zrób sobie mózg https://www.tygodnikprzeglad.pl/zrob-sobie-mozg/. Przegląd (6/2018): pp. 58–59.

“When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble.. If we ignore the existence of loops and permit the nodes to continue communicating with each other as if the network were singly connected, messages may circulate indefinitely around the loops and process may not converges to a stable equilibrium… Such oscillations do not normally occur in probabilistic networks… which tend to bring all messages to some stable equilibrium as time goes on. However, this asymptotic equilibrium is not coherent, in the sense that it does not represent the posterior probabilities of all nodes of the network.”

Judea Pearl (1936) Computer scientist

Source: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, 1988, p. 195

“Everywhere networks go, intermediaries follow. The more nodes, the more middlemen.”

Kevin Kelly (1952) American author and editor

Out of Control: The New Biology of Machines, Social Systems and the Economic World (1995), New Rules for the New Economy: 10 Radical Strategies for a Connected World (1999)

“The function of knowledge in the decision-making process is to determine which consequences follow upon which of the alternative strategies. It is the task of knowledge to select from the whole class of possible consequences a more limited subclass, or even (ideally) a single set of consequences correlated with each strategy.”

Herbert A. Simon book Administrative Behavior

Source: 1940s-1950s, Administrative Behavior, 1947, p. 78.

“Neural Computing is the study of networks of adaptable nodes which through a process of learning from task examples, store experiential knowledge and make it available for use.”

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