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  2. AI safety - Wikipedia

    en.wikipedia.org/wiki/AI_safety

    AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.

  3. MBS College for Cybersecurity and Advanced Technologies

    en.wikipedia.org/wiki/MBS_College_for_Cyber...

    Prior to its official inauguration in April 2018, the college was renamed as the Prince Mohammed bin Salman College for Cyber Security, Artificial Intelligence and Advanced Technologies after getting the crown prince's assent for the renaming proposal put forward by the Saudi Federation for Cybersecurity, Programming and Drones. Dr.

  4. Applications of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Applications_of_artificial...

    Cyber security companies are adopting neural networks, machine learning, and natural language processing to improve their systems. [51] Applications of AI in cyber security include: Network protection: Machine learning improves intrusion detection systems by broadening the search beyond previously identified threats.

  5. Regulation of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Regulation_of_artificial...

    [141] [142] In terms of cyber security, in 2020 the National Cyber Security Centre has issued guidance on 'Intelligent Security Tools'. [ 46 ] [ 143 ] The following year, the UK published its 10-year National AI Strategy, [ 144 ] which describes actions to assess long-term AI risks, including AGI-related catastrophic risks.

  6. 1 No-Brainer Artificial Intelligence (AI) Stock to Buy With ...

    www.aol.com/1-no-brainer-artificial-intelligence...

    SentinelOne (NYSE: S) is a fast-growing provider of cybersecurity software with artificial intelligence (AI) at its core. It stands to benefit significantly as the spending gap highlighted by ...

  7. Cybersecurity engineering - Wikipedia

    en.wikipedia.org/wiki/Cybersecurity_engineering

    Concepts like layered security architecture and the use of artificial intelligence for threat detection became critical. The integration of frameworks such as the NIST Cybersecurity Framework emphasized the need for a comprehensive approach that includes technical defense, prevention, response, and incident recovery.

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