IEML: rumo a uma mudança de paradigma na Inteligência Artificial
DOI :
https://doi.org/10.11606/issn.1982-8160.v16i1p11-34Mots-clés :
Inteligência artificial, Código semântico, Inteligência coletiva, MetaLinguagem da Economia da InformaçãoRésumé
O objetivo deste ensaio é apresentar uma visão geral das limitações da Inteligência Artificial (IA) contemporânea e propor uma abordagem para superá-las com uma metalinguagem semântica computável. Proponho que a IA adote um modelo computável e univocal da linguagem humana, a MetaLinguagem da Economia da Informação, um código semântico de minha própria invenção que tem o poder expressivo de uma linguagem natural e a sintaxe de uma linguagem regular. Isso pode abrir novos caminhos para a IA criar uma sinergia entre a democratização do controle de dados e o aprimoramento da inteligência coletiva.
##plugins.themes.default.displayStats.downloads##
Références
Berners-Lee, T. (1999). Weaving the Web. Harper.
Bush, V. (1945, julho). As we may think. Atlantic Monthly.
Chomsky, N. (1957). Syntaxic structures. Mouton.
Chomsky, N., & Schützenberger, M.-P. (1963). The algebraic theory of context-free languages. In P. Braffort & D. Hirschberg (Eds.), Computer Programming and Formal Languages (pp. 118-161).
Chomsky, N. (2000). New horizons in the study of language and mind. Cambridge UP.
Engelbart, D. (1962). Augmenting human intellect [Relatório técnico]. Stanford Research Institute.
Ernst, D. (2020). AI research and governance are at a crossroads. CIGI Online. https://www.cigionline.org/articles/ai-research-and-governance-are-crossroads/
Garcez, A. A., & Lamb, L. C. (2020). Neurosymbolic AI: The 3rd Wave. https://arxiv.org/pdf/2012.05876.pdf
Kripke, S. (1980). Naming and Necessity. Blackwell.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436-444. https://doi.org/10.1038/nature14539
Lévy, P. (1986). Analyze de contenu des travaux du Biological Computer Laboratory (BCL). Cahiers du CREA, 8, 155-191.
Lévy, P. (1986). L’Œuvre de Warren McCulloch. Cahiers du CREA, 7, 211-255.
Lévy, P. (1991). Les systèmes à base de connaissance comme médias de transmission de l’expertise. Intellectica, 12, 187-219.
Lévy, P. (1992). De la programmation considérée comme un des beaux-arts. La Découverte.
Lévy, P. (1994). L’intelligence collective, pour une anthropologie du cyberespace. La Découverte. Edição inglesa: Lévy, P. (1997). Collective intelligence (R. Bonono, Trans.). Perseus Books.
Lévy, P. (2009). Toward a self-referential collective intelligence: Some philosophical background of the IEML research program. In N. T. Nguyen, R. Kowalczyk & C. Shyi-Ming (Eds.), Computational collective intelligence, semantic web, social networks and multiagent systems. First International Conference, ICCCI, Wroclaw, Poland, Oct. 2009, Proceedings (pp. 22-35). Springer.
Lévy, P. (2010, 2 de janeiro). The IEML research program: From social computing to reflexive collective intelligence. Information sciences, special issue on collective intelligence, 180(1), 71-94.
Lévy, P. (2011). The semantic sphere. Computation, cognition and information economy. Wiley.
Lévy, P. (2021). Proper nouns in IEML. Intlekt. https://intlekt.io/proper-names-in-ieml/
Lévy, P. (2021). The linguistic roots of IEML. Intlekt. https://intlekt.io/the-linguistic-roots-of-ieml/
Licklider, J. (1960). Man-computer symbiosis. IRE Transactions on human factors in electronics, 1, 4-11.
Marcus, G., & Davis, E. (2019). Rebooting AI: Building artificial intelligence we can trust. Vintage.
McClelland, J. L., Rumelheart, D. E., & PDP Research Group. (1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition. 2 vols. MIT Press.
McCulloch, W. S. (1965). Embodiments of mind. MIT Press.
McCulloch, W. S., & Pitts, W. (1943). A logical calculus of ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 5, 115-133. https://doi.org/10.1007/BF02478259
Minsky, M. & Papert, S. (1969). Perceptrons, MIT Press.
Minsky, M. (1986). The Society of Mind. Simon and Schuster.
Pearl, J., & Mackenzie, D. (2019). The book of why: The new science of cause and effect. Basic Books.
Popper, K. (1972). Objective knowledge: An evolutionary approach. Clarendon Press.
Rosenblatt, F. (1962). Principles of neurodynamics: Perceptrons and the theory of brain mechanisms. Spartan Books.
Rumelhart, D. E., Hinton, G. E., Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323(6088), 533-536. https://doi.org/10.1038/323533a0
von Foerster, H. (1981). Observing Systems: Selected Papers of Heinz von Foerster, Intersystems Publications.
Téléchargements
Publiée
Numéro
Rubrique
Licence
(c) Copyright Pierre Lévy 2022
Ce travail est disponible sous licence Creative Commons Attribution - Pas d’Utilisation Commerciale - Partage dans les Mêmes Conditions 4.0 International.
Les auteurs qui publient dans ce journal acceptent les termes suivants:
- Les auteurs conservent le droit d'auteur et accordent à la revue le droit de première publication, le travail étant concédé simultanément sous la licence Creative Commons Attribution (CC BY-NC-SA 4.0) qui permet le partage de l'œuvre avec reconnaissance de la paternité et de la publication initiale dans cette revue à des fins non commerciales.
- Les auteurs sont autorisés à assumer des contrats supplémentaires séparément, pour une distribution non exclusive de la version de l'ouvrage publiée dans cette revue (par exemple, publication dans un référentiel institutionnel ou en tant que chapitre de livre), avec reconnaissance de la paternité et de la publication initiale dans cette revue.
