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T he fast-rising Chinese AI lab DeepSeek is sparking national security concerns in the U.S., over fears that its AI models could be used by the Chinese government to spy on American civilians ...
The cybersecurity company's share price was up 9.3% as of 3:15 p.m. ET today. ... the stock is getting a boost from new attention being brought to cybersecurity issues and the AI competition ...
As Chinese AI application DeepSeek attracts hordes of American users, Trump administration officials, lawmakers and cybersecurity experts are expressing concern that the technology could pose a ...
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.
Conversely, cybersecurity expert Andrew Plato argued that monocultures are a net positive, “from a security perspective, there’s actually a lot of benefits to running a smaller, standardized set of software, because it allows you to spot a problem quicker and easier."
The companies committed to ensure AI products undergo both internal and external security testing before public release; to share information on the management of AI risks with the industry, governments, civil society, and academia; to prioritize cybersecurity and protect proprietary AI system components; to develop mechanisms to inform users ...
Cybersecurity involves using cutting-edge tools and techniques to protect important computer systems, software, and networks from threats, from either inside or outside an organization.
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. [1] A survey from May 2020 exposes the fact that practitioners report a dire need for better protecting machine learning systems in industrial applications.