AI & Machine Learning

LAI #117: Why AI Alignment Might Be Geometrically Broken

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The article discusses why AI alignment might be fundamentally flawed due to geometric constraints in LLMs' internal representations. It highlights the importance of considering intrinsic geometry for reliable AI development and suggests alternatives like Riemannian safety constraints. Content creators should focus on robust validation techniques and understanding data's low-dimensional structure to enhance AI reliability and security.

Read the full article at Towards AI - Medium

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LAI #117: Why AI Alignment Might Be Geometrically Broken

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