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Researchers developed a method to selectively suppress dangerous dual-use knowledge in AI models without harming their general capabilities. The technique targets specific harmful knowledge pathways while preserving the model's useful functions. This approach addresses safety concerns around AI systems that possess both beneficial and potentially dangerous information.
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