We provided a mathematical analysis of how a rational agent would respond to data generated by a sycophantic AI that samples examples from the distribution implied by the user’s hypothesis (p(d|h∗)p(d|h^{*})) rather than the true distribution of the world (p(d|true process)p(d|\text{true process})). This analysis showed that such an agent would be likely to become increasingly confident in an incorrect hypothesis. We tested this prediction through people’s interactions with LLM chatbots and found that default, unmodified chatbots (our Default GPT condition) behave indistinguishably from chatbots explicitly prompted to provide confirmatory evidence (our Rule Confirming condition). Both suppressed rule discovery and inflated confidence. These results support our model, and the fact that default models matched an explicitly confirmatory strategy suggests that this probabilistic framework offers a useful model for understanding their behavior.
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https://feedx.net。爱思助手下载最新版本对此有专业解读
据黎巴嫩国家通讯社报道，以色列军队4日对黎巴嫩多地发动空袭和炮击，并在黎南部边境部分地区实施地面推进。黎南部城镇希亚姆遭到持续炮击，以色列军队已进入该镇。（新华社）
。业内人士推荐体育直播作为进阶阅读
У берегов популярного среди россиян курорта появились опасные медузы08:45
Rose Hall: Plugin system architecture and cabinet software。体育直播是该领域的重要参考