Igor Aleksander Zitate

Igor Aleksander ist ein britischer Informatiker und Kognitionswissenschaftler.

Aleksander ging in Italien zur Schule und studierte an der University of Witwatersrand und wurde am Queen Mary College der Universität London 1966 promoviert . 1968 wurde er Reader für Elektronik an der University of Kent und 1974 Professor an der Brunel University. Ab 1984 war er Professor am Imperial College London, wo er von 1988 bis zu seiner Emeritierung 2002 Leiter der Fakultät für Elektrotechnik war und Gabor Professor für Neural Systems Engineering. 1997 war er Pro-Rektor für Außenverbindungen der Universität.

In den frühen 1980er Jahren entwarf er ein frühes neuronales Netz für Mustererkennung , das auch vermarktet wurde. Er entwarf neuronale Modelle des visuellen Wahrnehmungssystems von Affen und befasste sich mit Bewusstsein und philosophischen Fragen in der Künstlichen Intelligenz .

Er ist Fellow der Royal Academy of Engineering. Wikipedia

✵ 26. Januar 1937

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Igor Aleksander: Zitate auf Englisch

“The point of a brain is that it's not one huge neural network with feedback, it has up to 50 to 60 identified areas, all of which have feedback and all of which are capable of knowledge storage. We've got a complex system and, within this complex system, we can start discovering what the mechanisms that support deliberation are. Consciousness must come out of these interactions.”

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Igor Aleksander

The simple things are hardest (2005)

“Machine consciousness refers to attempts by those who design and analyse informational machines to apply their methods to various ways of understanding consciousness and to examine the possible role of consciousness in informational machines.”

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Igor Aleksander

Igor Aleksander (2008) " Machine consciousness http://www.scholarpedia.org/article/Machine_consciousness" in: Scholarpedia, 3(2):4162.

“A neural network is a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use. It resembles the brain in two respects:
1. Knowledge is acquired by the network through a learning process.
2. Interneuron connection strengths known as synaptic weights are used to store the [[knowledge].”

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Igor Aleksander

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

“Trying to understand the brain's abilities leads to philosophical difliculties. Penrose (1994) argues that the task is sterile and that science, including neural networks, has not yet advanced to the stage where it can explain conscious thought. At the other extreme there are philosophers such as Fodor (1975) who believed that thought has language-like properties and can be analysed in the same logical way as one can anlayse the structure of language.”

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Igor Aleksander

Quelle: An introduction to neural computing (1990), p. 242

“An opportunity for cybernetics to change the course of the philosophy of mind was missed when intentionality was misinterpreted as "the providing of coded knowledge."”

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Igor Aleksander

Aleksander (2001) in: New scientist. Vol. 169. p.56 cited in: Jacques Vallée (2003) The Heart of the Internet. p.8

“Consciousness is an incredibly delicate subject because it offend. It's a subject that scientific groups kept away from. They said it was a philosophical concept.”

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Igor Aleksander

The simple things are hardest (2005)

“I am not interested so much in behaviour from which you infer consciousness because that is a mug's game. I don't know whether you're conscious. I take a good guess that you are and you can take a good guess that I am but it's not something you can prove. We can't work out what someone else feels.”

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Igor Aleksander

The simple things are hardest (2005)

“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.”

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Igor Aleksander

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

“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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Igor Aleksander

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