AI-assisted virtualization software: Difference between revisions

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Impact and applications: Buzzwords and peacock words
Future prospects: Again, Wikipedia isn't a platform for advocacy or hype. Buzzwords and informal cliches should be avoided, and vague generalizations need to be a attributed to a specific, reliable source.
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== Challenges ==
Despite its many advantages, AI-assisted virtualization software is not without its challenges. Implementing this type of software requires a high degree of technological sophistication and can incur significant costs. There are also concerns about the risks associated with AI, such as algorithmic bias and security vulnerabilities. Additionally, there are issues related to governance, ethics, and regulations of AI technologies.<ref>{{Cite book |last1=Rawat |first1=Danda B. |title=Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation |last2=Awasthi |first2=Lalit K |last3=Balas |first3=Valentina Emilia |last4=Kumar |first4=Mohit |last5=Samriya |first5=Jitendra Kumar |publisher=Scrivener Publishing LLC |year=2023 |isbn=9781119904885}}</ref>
 
== Future prospects ==
As the fields of AI and virtualization continue to evolve, AI-assisted virtualization software is expected to become more advanced and integrated into an even wider range of applications. Future trends may include advanced self-healing systems, integration with quantum computing, and the development of more sophisticated AI models that can autonomously manage increasingly complex virtual environments.<ref>{{Cite book |date=2020 |editor-last=Hemanth |editor-first=Jude |editor2-last=Bhatia |editor2-first=Madhulika |editor3-last=Geman |editor3-first=Oana |url=http://dx.doi.org/10.1007/978-3-030-25797-2 |volume=32 |doi=10.1007/978-3-030-25797-2 |isbn=978-3-030-25796-5 |s2cid=241311770 |issn=2367-4512 |title=Data Visualization and Knowledge Engineering |series=Lecture Notes on Data Engineering and Communications Technologies }}</ref>
 
== See also ==