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Illustration of the proposed QuadAttackK method compared with the previous technique (e.g., adversarial distillation (AD) method (Zhang and Wu, 2020)).
A new study finds AI tools are more vulnerable than previously thought to targeted attacks that effectively force AI systems to make bad decisions.
Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images -- however, there are significant challenges related to both computing power requirements and decision-making transparency. Researchers have now developed a new methodology that addresses both challenges, while also improving the ViT's ability to identify, classify and segment objects in images.
Vision transformers (ViTs) are considered to be strong artificial intelligence (AI) technologies that have the potential to determine or classify objects in images.
Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images – however, there are significant challenges related to both computing power requirements and decision-making transparency. Researchers have now developed a new methodology that addresses both challenges, while also improving the ViT’s ability to identify, classify and segment objects in images.