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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.
Cybersecurity engineering is a tech discipline focused on the protection of systems, networks, and data from unauthorized access, cyberattacks, and other malicious activities. It applies engineering principles to the design, implementation, maintenance, and evaluation of secure systems, ensuring the integrity, confidentiality, and availability ...
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Incorporation of AI in federal government operations with CISA guidance. The federal government isn't planning to sit on the sidelines and merely set the rules for the rest of the players.
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.
Artificial intelligence engineering (AI engineering) is a technical discipline that focuses on the design, development, and deployment of AI systems. AI engineering involves applying engineering principles and methodologies to create scalable, efficient, and reliable AI-based solutions.
The National Security Commission on Artificial Intelligence (NSCAI) was an independent commission of the United States of America established in 2018 to make recommendations to the President and Congress to "advance the development of artificial intelligence, machine learning, and associated technologies to comprehensively address the national security and defense needs of the United States".
A David Binder Research poll commissioned by the Center for AI Safety, a group focused on mitigating societal-scale risk and a sponsor of the bill, found that 77% of Californians support a proposal to require companies to test AI models for safety risks, and 86% consider it an important priority for California to develop AI safety regulations.