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Yann LeCun says AI systems built around world models could offer a different approach to safety than today’s large language models. At a Seoul briefing, he argued that a sudden AI takeover belongs closer to science fiction, while acknowledging that a world model could still make a dangerous mistake if it predicts reality incorrectly.

LeCun’s proposal is for systems that predict the consequences of their actions and follow predefined goals and safety constraints. He also argued that current LLMs are difficult to make reliably safe across every possible question. Those are his views, as reported by DigitalToday, not evidence that world models have solved the problem. The distinction matters: a system designed to anticipate what its actions will do is a different safety bet from trying to tune a language model to avoid every harmful answer. But the consequences still depend on whether its predictions and safeguards work outside the drawing board.

Discuss: Should AI safety rely more on designing systems around world models, or on testing and constraining the models we already use?

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