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Artificial Intelligence Implementations on the Blockchain. Use Cases and Future Applications

Author

Listed:
  • Konstantinos Sgantzos

    (Department of Computer Science and Biomedical Informatics, University of Thessaly, 35100 Lamia, Greece)

  • Ian Grigg

    (YangSec Ltd, MST9051 Mosta, Malta)

Abstract

An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of a dataset for machine learning by an AI entity. Datasets can be very expensive to purchase, as, depending on both the proper selection of the elements and the homogeneity of the data contained within, constructing and maintaining the integrity of a dataset is difficult. Blockchain as a highly secure storage medium presents a technological quantum leap in maintaining data integrity. Furthermore, blockchain’s immutability constructs a fruitful environment for creating high quality, permanent and growing datasets for deep learning. The combination of AI and blockchain could impact fields like Internet of things (IoT), identity, financial markets, civil governance, smart cities, small communities, supply chains, personalized medicine and other fields, and thereby deliver benefits to many people.

Suggested Citation

  • Konstantinos Sgantzos & Ian Grigg, 2019. "Artificial Intelligence Implementations on the Blockchain. Use Cases and Future Applications," Future Internet, MDPI, vol. 11(8), pages 1-15, August.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:8:p:170-:d:254170
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    Citations

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    Cited by:

    1. Vincent Charles & Ali Emrouznejad & Tatiana Gherman, 2023. "A critical analysis of the integration of blockchain and artificial intelligence for supply chain," Annals of Operations Research, Springer, vol. 327(1), pages 7-47, August.
    2. Rashi Saxena & E. Gayathri & Lalitha Surya Kumari, 2023. "Semantic analysis of blockchain intelligence with proposed agenda for future issues," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 34-54, March.
    3. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    4. Naoum Tsolakis & Roman Schumacher & Manoj Dora & Mukesh Kumar, 2023. "Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?," Annals of Operations Research, Springer, vol. 327(1), pages 157-210, August.
    5. Konstantinos Sgantzos & Ian Grigg & Mohamed Al Hemairy, 2022. "Multiple Neighborhood Cellular Automata as a Mechanism for Creating an AGI on a Blockchain," JRFM, MDPI, vol. 15(8), pages 1-24, August.
    6. Rameez Asif & Syed Raheel Hassan & Gerard Parr, 2023. "Integrating a Blockchain-Based Governance Framework for Responsible AI," Future Internet, MDPI, vol. 15(3), pages 1-21, February.
    7. Vasiliy Elagin & Anastasia Spirkina & Andrei Levakov & Ilya Belozertsev, 2020. "Blockchain Behavioral Traffic Model as a Tool to Influence Service IT Security," Future Internet, MDPI, vol. 12(4), pages 1-12, April.

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