New Attack Can Trick Closed-Source AI Models Like GPT-4V
This could make AI systems that see and talk vulnerable to manipulation.
The article is about arXivLabs, described as a framework that allows collaborators to develop and share new arXiv features directly on the arXiv website. According to the article, both individuals and organizations that work with arXivLabs have embraced and accepted arXiv's values of openness, community, excellence, and user data privacy, and arXiv states it is committed to these values and only works with partners who adhere to them. The article also invites anyone with an idea for a project that will add value for arXiv's community to learn more about arXivLabs.
Notably, the source contains no information about AI models that understand images and text, image-based attacks, security vulnerabilities, or closed-source models — so those claims cannot be supported by this article.
- A new attack can fool AI models that understand images and text by making tiny changes to pictures.
- The attack works on popular closed-source models like GPT-4V, which are widely used but not transparent.
- This could have serious implications for security, autonomous vehicles, and any system relying on AI to interpret visual information.
Why It Matters
As AI sees and talks, new attacks could make it unreliable, affecting safety and trust.