——"诱导式学习(causal learning)与诊断式学习(diagnostic learning)前者是指对已有人物和事件及其他人给予的缘故原由解释的学习后者是指对正在发生的人物和事件举...
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Thus learning effects are theoretically distinct from scale effects, even if in practice they my be hard to differentiate due to e.g. uncertainty and causal ambiguity.
所以理论上学习效应和规模效应不同，尽管实际操作中由于不确定性和模糊的因果关系可能很难区分它们。
Although we have not yet reached that eureka moment where a direct causal link between learning languages and specific cognitive advantages can be proven, the -evidence is building up fast.
尽管我们尚未获得令人惊叹的在学习语言和特定认知优势被正式的直接因果联系，但是，证据的积累在加快。
One area that's going to get a lot of attention is combining machine learning with causal inference.
未来有一个领域将会得到很多的关注，那就是将机器学习与因果推理相结合。
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