Abstract
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.
Highlights
Who mowed the lawn, Ambrogio1 or Alice? We know that the two are different in everything: bodily, “cognitively”, and “behaviourally”
In the same way as Google “reads” our queries without understanding them, and offers relevant answers, likewise, GPT-3 writes a text continuing the sequence of our words, without any understanding
Curious to know more about the limits of GPT-3 and the many speculations surrounding it, we decided to run three tests, to check how well it performs with logicomathematical, sematic, and ethical requests
Summary
Ambrogio (a robotic lawn mower) or Alice? We know that the two are different in everything: bodily, “cognitively” (in terms of internal information processes), and “behaviourally” (in terms of external actions). There is a sense in which Turing was right: plenty of questions can be answered irreversibly by computers today, and the way we think and speak about machines has changed. GPT-3 (Generative Pre-trained Transformer) is a third-generation, autoregressive language model that uses deep learning to produce human-like text. To put it more it is a computational system designed to generate sequences of words, code or other data, starting from a source input, called the prompt. In the same way as Google “reads” our queries without understanding them, and offers relevant answers, likewise, GPT-3 writes a text continuing the sequence of our words (the prompt), without any understanding.
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