tty.setraw(sys.stdin)
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.
。业内人士推荐heLLoword翻译官方下载作为进阶阅读
Copyright © 1997-2026 by www.people.com.cn all rights reserved
圖像加註文字，台灣每年二二八都有紀念活動Article InformationAuthor, 黃奕瀠
。关于这个话题，旺商聊官方下载提供了深入分析
Get Tom's Hardware's best news and in-depth reviews, straight to your inbox.
Are you also playing NYT Strands? Get all the Strands hints you need for today's puzzle.，更多细节参见体育直播