Economics Dictionary of ArgumentsHome![]() | |||
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Neural networks: Neural networks are computational models inspired by the human brain, designed to recognize patterns and solve complex problems. They consist of layers of interconnected nodes (analogous to neurons) that process input data and learn to perform tasks by adjusting the strength of connections based on feedback. Used extensively in machine learning, they enable applications like image recognition, language processing, and predictive analysis. See also Artificial Neural networks, Connectionism, Computer models, Computation, Artificial Intelligence, Machine learning._____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. | |||
Author | Concept | Summary/Quotes | Sources |
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Stephen Wolfram on Neural Networks - Dictionary of Arguments
Brockman I 270 Neural networks/Wolfram: In i 943, Warren McCulloch and Walter Pitts came up with a model for how brains conceptually, formally, might work—an artificial neural network. They saw that their brainlike model would do computations in the same way as Turing Machines. From their work, it emerged that we could make brainlike neural networks that would act as general computers. And in fact, the practical work done by the ENIAC folks and John von Neumann and others on computers came directly not from Turing Machines but through this bypath of neural networks. >Turing-Machine. Brockman I 271 Perceptron/Rosenblatt: Frank Rosenblatt invented a learning device which was a one-layer neural network. MinskyVsRosenblatt/PapertVsRosenblatt: perceptrons couldn’t do anything interesting. Wolfram: this was correct. Perceptrons could make only linear distinctions between things. >Artificial intelligence/Wolfram. Wolfram, Stephen (2015) „Artificial Intelligence and the Future of Civilization” (edited live interview), in: Brockman, John (ed.) 2019. Twenty-Five Ways of Looking at AI. New York: Penguin Press._____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition. |
Wolfram, Stephen Brockman I John Brockman Possible Minds: Twenty-Five Ways of Looking at AI New York 2019 |