In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic (that is, the Turing Test), and ethical questions and show that GPT-3 is not designed to pass any of them. This is a reminder that GPT-3 does not do what it is not supposed to do, and that any interpretation of GPT-3 as the beginning of the emergence of a general form of artificial intelligence is merely uninformed science fiction. We conclude by outlining some of the significant consequences of the industrialisation of automatic and cheap production of good, semantic artefacts.

中文翻译：

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GPT-3：其性质、范围、限制和后果

在这篇评论中，我们讨论可逆和不可逆问题的性质，即可以使人们确定其答案来源的性质的问题。然后我们介绍 GPT-3，这是第三代自回归语言模型，它使用深度学习来生成类人文本，并使用之前的区别对其进行分析。我们将分析扩展到提出基于数学、语义（即图灵测试）和伦理问题的三个测试，并表明 GPT-3 并非旨在通过其中任何一个。这提醒我们 GPT-3 不会做它不应该做的事情，任何将 GPT-3 解释为通用人工智能形式出现的开始都只是无知的科幻小说。