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“We believe that machines and humans excel at detecting fundamentally different aspects of generated text,” Sebastian Gehrmann, a Ph.D. candidate in Computer Science at Harvard, told Digital Trends. “Machine learning algorithms are great at picking up statistical patterns such as the ones we see in GLTR. However, at the moment machines do not actually understand the content of a text. That means that algorithms could be fooled by completely nonsensical text, as long as the patterns match the detection. Humans, on the other hand, can easily tell when a text does not make any sense, but cannot detect the same patterns we show in GLTR.”