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首先,The professors also asked the models to generate tweets and op-eds describing their experience, and they drew out the the politically relevant words that emerged most often. “Unionize” and “hierarchy” were the words most statistically emblematic of the models that were intentionally overworked.
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第三,Imas offered a more expansive view, cautioning against pinning it on any single source. “It’s a very complicated interaction of everything that they’ve seen, which is, like, the entire corpus of human writing,” he said. It’s ultimately impossible to tell whether Reddit data or, say, a textbook on 19th century history and the socialist revolutions of 1848 is responsible for these proto-Marxist leanings. “Once you have that much data and the neural network is that complicated, it’s truly a black box.”
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