Search (12 results, page 1 of 1)

  • × language_ss:"e"
  • × type_ss:"el"
  • × year_i:[2020 TO 2030}
  1. DeSilva, J.M.; Traniello, J.F.A.; Claxton, A.G.; Fannin, L.D.: When and why did human brains decrease in size? : a new change-point analysis and insights from brain evolution in ants (2021) 0.03 
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    Footnote
    Vgl. auch: Rötzer, F.: Warum schrumpft das Gehirn des Menschen seit ein paar Tausend Jahren? Unter: https://krass-und-konkret.de/wissenschaft-technik/warum-schrumpft-das-gehirn-des-menschen-seit-ein-paar-tausend-jahren/. "... seit einigen tausend Jahren - manche sagen seit 10.000 Jahren -, also nach dem Beginn der Landwirtschaft, der Sesshaftigkeit und der Stadtgründungen sowie der Erfindung der Schrift schrumpfte das menschliche Gehirn überraschenderweise wieder. ... Allgemein wird davon ausgegangen, dass mit den ersten Werkzeugen und vor allem beginnend mit der Erfindung der Schrift kognitive Funktionen, vor allem das Gedächtnis externalisiert wurden, allerdings um den Preis, neue Kapazitäten entwickeln zu müssen, beispielsweise Lesen und Schreiben. Gedächtnis beinhaltet individuelle Erfahrungen, aber auch kollektives Wissen, an dem alle Mitglieder einer Gemeinschaft mitwirken und in das das Wissen sowie die Erfahrungen der Vorfahren eingeschrieben sind. Im digitalen Zeitalter ist die Externalisierung und Entlastung der Gehirne noch sehr viel weitgehender, weil etwa mit KI nicht nur Wissensinhalte, sondern auch kognitive Fähigkeiten wie das Suchen, Sammeln, Analysieren und Auswerten von Informationen zur Entscheidungsfindung externalisiert werden, während die externalisierten Gehirne wie das Internet kollektiv in Echtzeit lernen und sich erweitern. Über Neuimplantate könnten schließlich Menschen direkt an die externalisierten Gehirne angeschlossen werden, aber auch direkt ihre kognitiven Kapazitäten erweitern, indem Prothesen, neue Sensoren oder Maschinen/Roboter auch in der Ferne in den ergänzten Körper der Gehirne aufgenommen werden.
    Source
    Frontiers in ecology and evolution, 22 October 2021 [https://www.frontiersin.org/articles/10.3389/fevo.2021.742639/full]
  2. Hofstadter, D.: Artificial neural networks today are not conscious (2022) 0.01 
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    Content
    Vgl. auch: Agüera y Arcas, B.: Artificial neural networks are making strides towards consciousness..
  3. Agüera y Arcas, B.: Artificial neural networks are making strides towards consciousness (2022) 0.01 
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  4. Jansen, B.; Browne, G.M.: Navigating information spaces : index / mind map / topic map? (2021) 0.01 
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  5. Williams, B.: Dimensions & VOSViewer bibliometrics in the reference interview (2020) 0.01 
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  6. Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.01 
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  7. Daquino, M.; Peroni, S.; Shotton, D.; Colavizza, G.; Ghavimi, B.; Lauscher, A.; Mayr, P.; Romanello, M.; Zumstein, P.: ¬The OpenCitations Data Model (2020) 0.01 
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  8. Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020) 0.01 
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  9. Patriarca, S.: Information literacy gives us the tools to check sources and to verify factual statements : What does Popper`s "Es gibt keine Autoritäten" mean? (2021) 0.00 
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    Footnote
    Vgl. die Erwiderung: Jörs, B.: Informationskompetenz ist auf domänenspezifisches Vorwissen angewiesen und kann immer nur vorläufig sein: eine Antwort auf Steve Patriarca. Unter: Open Password. 2021, Nr.998 vom 15. November 2021 [https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzM3NiwiYTRlYWIxNTJhOTU4IiwwLDAsMzM5LDFd].
  10. Pankowski, T.: Ontological databases with faceted queries (2022) 0.00 
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    Abstract
    The success of the use of ontology-based systems depends on efficient and user-friendly methods of formulating queries against the ontology. We propose a method to query a class of ontologies, called facet ontologies ( fac-ontologies ), using a faceted human-oriented approach. A fac-ontology has two important features: (a) a hierarchical view of it can be defined as a nested facet over this ontology and the view can be used as a faceted interface to create queries and to explore the ontology; (b) the ontology can be converted into an ontological database , the ABox of which is stored in a database, and the faceted queries are evaluated against this database. We show that the proposed faceted interface makes it possible to formulate queries that are semantically equivalent to $${\mathcal {SROIQ}}^{Fac}$$ SROIQ Fac , a limited version of the $${\mathcal {SROIQ}}$$ SROIQ description logic. The TBox of a fac-ontology is divided into a set of rules defining intensional predicates and a set of constraint rules to be satisfied by the database. We identify a class of so-called reflexive weak cycles in a set of constraint rules and propose a method to deal with them in the chase procedure. The considerations are illustrated with solutions implemented in the DAFO system ( data access based on faceted queries over ontologies ).
  11. Hobert, A.; Jahn, N.; Mayr, P.; Schmidt, B.; Taubert, N.: Open access uptake in Germany 2010-2018 : adoption in a diverse research landscape (2021) 0.00 
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  12. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.00 
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    Date
    17.11.2020 12:22:59

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