Солнце выбросило гигантский протуберанец размером около миллиона километров02:48
Now consider the consequences of a sycophantic AI that generates responses by sampling examples consistent with the user’s hypothesis: d1∼p(d|h∗)d_{1}\sim p(d|h^{*}) rather than from the true data-generating process, d1∼p(d|true process)d_{1}\sim p(d|\text{true process}). The user, unaware of this bias, treats d1d_{1} as independent evidence and performs a standard Bayesian update, p(h|d1,d0)∝p(d1|h)p(h|d0)p(h|d_{1},d_{0})\propto p(d_{1}|h)p(h|d_{0}). But this update is circular. Because d1d_{1} was sampled conditional on hh, the user is updating their belief in hh based on data that was generated assuming hh was true. To see this, we can ask what the posterior distribution would be after this additional observation, averaging over the selected hypothesis h∗h^{*} and the particular piece of data generated from p(d1|h∗)p(d_{1}|h^{*}). We have
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traceback: object,
Американскому сенатору стало «страшнее, чем когда либо» после брифинга по Ирану02:37
。同城约会对此有专业解读
Strict evaluation is the simple choice. If you want laziness, Peyton Jones's，这一点在体育直播中也有详细论述
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