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Artificial intelligence and IoT based optical quantum computing application legal implications in privacy and regulatory analysis.
- Source :
-
Optical & Quantum Electronics . Apr2024, Vol. 56 Issue 4, p1-18. 18p. - Publication Year :
- 2024
-
Abstract
- Parallel developments in the realms of AI and quantum technology have shown a great deal of promise for mutual benefit. Combining them refers to using AI methods to create quantum computing (QC) and quantum physics algorithms as well as using QC to improve AI applications. QC has the power to revolutionise a number of industries. One of the biggest barriers preventing the broad application of QC is the famously challenging nature of controlling quantum systems. AI has made it possible to automate quantum system control in novel ways. In particular, the use of AI in conjunction with the Internet of Things (IoT) can potentially ease problems that have historically been connected to QC and quantum communication while revealing invaluable insight into the intricate and multifaceted field of quantum physics. However, QC may also be applied to improve AI applications. This study tries to examine how these technologies are used in the judicial system and how they affect courtroom behaviour. Accelerators are necessary for the quick and efficient execution of artificial intelligence activities across a variety of applications. Despite a half-century of study, general-purpose optical computing methods still haven't developed into a workable technology. However, optical computing methods may be able to address certain domain-specific demands. The focus of the article is on how these technologies may increase the efficacy and efficiency of law enforcement and the legal system, rather than providing a thorough examination of the legal system. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03068919
- Volume :
- 56
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Optical & Quantum Electronics
- Publication Type :
- Academic Journal
- Accession number :
- 175877614
- Full Text :
- https://doi.org/10.1007/s11082-023-06161-1