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Blockchain und maschinelles Lernen – Ein Literaturüberblick

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Blockchain und maschinelles Lernen

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Zusammenfassung

Blockchain und maschinelles Lernen sind zwei der vielversprechendsten Technologien unserer Zeit. Obgleich vielen nur durch Kryptowährungen und selbstfahrende Autos bekannt und greifbar, sind die Potenzial viel weitreichender. Jede neue Technologie bringt neben teils umwälzenden Veränderungen auch viele neue Herausforderungen mit sich, die verhindern, dass diese ihr volles Potenzial entfalten können. Eine dieser Herausforderungen für das maschinelle Lernen stellt der enorme Bedarf an Daten, Hardware-Ressourcen und menschlicher Expertise dar. Ein zentrales Versprechen der Blockchain-Technologie hingegen ist die Demokratisierung gerade dieser Ressourcen. Hier kommt die Verschmelzung von Technologien ins Spiel, die nicht nur Herausforderungen bezwingen, sondern auch völlig neue Anwendungsformen erzeugen kann.

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Notes

  1. 1.

    Siehe hierzu auch den Beitrag DLT im Energiesektor in diesem Buch.

  2. 2.

    Swarm gehört zu der Gruppe der dezentral verteilten Storagelösungen, wie IPFS.

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Authors and Affiliations

  1. Besigheim, Deutschland

    Jerome Tagliaferri

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  1. Jerome Tagliaferri
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Correspondence to Jerome Tagliaferri .

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  1. Hochschule Heilbronn, Heilbronn, Germany

    Sigurd Schacht

  2. Hochschule Heilbronn, Heilbronn, Germany

    Carsten Lanquillon

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Tagliaferri, J. (2019). Blockchain und maschinelles Lernen – Ein Literaturüberblick. In: Schacht, S., Lanquillon, C. (eds) Blockchain und maschinelles Lernen. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-60408-3_4

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  • DOI: https://doi.org/10.1007/978-3-662-60408-3_4

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  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-60407-6

  • Online ISBN: 978-3-662-60408-3

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