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In this paper, we provide a rational analysis of the effects of sycophantic AI, considering how a Bayesian agent would respond to confirmatory evidence. Our analysis shows that such an agent will not get any closer to the truth, but will increase in their certainty about an incorrect hypothesis. We test this model in an online experiment where users are made to interact with an AI agent as they complete a rule discovery task. Our results show that the default interactions of a popular chatbot resemble the effects of providing people with confirmatory evidence, increasing confidence but bringing them no closer to the truth. These results provide a theoretical and empirical demonstration of how conversations with generative AI chatbots can facilitate delusion-like epistemic states, producing beliefs markedly divergent from reality.
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在测试中，机器人需在自攻螺母上件工站完成精准抓取与安装。小米团队通过端到端数据驱动的控制方法，结合 Vision-Language-Action 大模型 Xiaomi-Robotics-0 与强化学习框架，使机器人能够在复杂工况下保持稳定与高效。技术亮点包括：