Philosophy Dictionary of ArgumentsHome
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| Machine learning: Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values. See also Artificial Intelligence, Deep learning, Strong Artificial Intelligence, 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. | |||
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Neil Gershenfeld on Machine Learning - Dictionary of Arguments
Brockman I 165 Machine learning/Gershenfeld: It’s not possible to store all possible images in a self-driving car, or all possible sounds in a conversational computer; they have to be able to generalize from experience. The “deep” part of deep learning refers not to the (hoped-for) depth of insight but to the depth of the mathematical network layers used to make predictions. It turned out that a linear increase in network complexity led to an exponential increase in the expressive power of the network. >Learning, >Deep learning, >Neural networks, >Artificial neural networks, >Artificial Intelligence, >Strong Artificial Intelligence, >Artificial General Intelligence, >Human Level AI. Gershenfeld, Neil „Scaling”, 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. |
Gershenfeld, Neil Brockman I John Brockman Possible Minds: Twenty-Five Ways of Looking at AI New York 2019 |
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> Counter arguments against Gershenfeld
> Counter arguments in relation to Machine Learning
Ed. Martin Schulz, access date 2024-04-28