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We propose sycophancy leads to less discovery and overconfidence through a simple mechanism: When AI systems generate responses that tend toward agreement, they sample examples that coincide with users’ stated hypotheses rather than from the true distribution of possibilities. If users treat this biased sample as new evidence, each subsequent example increases confidence, even though the examples provide no new information about reality. Critically, this account requires no confirmation bias or motivated reasoning on the user’s part. A rational Bayesian reasoner will be misled if they assume the AI is sampling from the true distribution when it is not. This insight distinguishes our mechanism from the existing literature on humans’ tendency to seek confirming evidence; sycophantic AI can distort belief through its sampling strategy, independent of users’ bias. We formalize this mechanism and test it experimentally using a rule discovery task.
I started investigating why it crashes at accessing some memory, and found out that neither my debugger (lldb), nor Ghidra debugger can access that memory and it is shown as “unmapped”.。雷电模拟器官方版本下载对此有专业解读
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，更多细节参见51吃瓜
今年是三年集中整治攻坚决战之年，必须更好贯通各方责任、压实重点任务，加大力度、提高质效、形成机制，力争取得行风重塑、基层善治、群众受益的综合性成果。，这一点在17c 一起草官网中也有详细论述
SingleFile CLI: https://github.com/nitincodery/org-dex.el