Why does GPT-3 make those choices when most people choose the alternative? Because GPT-3 does not understand language the way humans do.
. Although GPT-3 did better than the older model, it was significantly worse than humans. It got the three scenarios mentioned above completely wrong.
GPT-3, the engine that powered the initial release of ChatGPT, learns about language by noting, from a trillion instances, which words tend to follow which other words. The strong statistical regularities in language sequences allow GPT-3 to learn a lot about language. And that sequential knowledge often allows ChatGPT to produce reasonable sentences, essays, poems and computer code.in human language, it doesn’t have the foggiest idea what any of those words mean to a human being.
Humans are biological entities that evolved with bodies that need to operate in the physical and social worlds to get things done. Language is a tool that helps people do that. GPT-3 is an artificial software system that predicts the next word. It does not need to get anything done with those predictions in the real world.intimately related to the human body
: people’s abilities to act, to perceive and to have emotions. Human cognition is empowered by being embodied. People’s understanding of a term like “paper sandwich wrapper,” for example, includes the wrapper’s appearance, its feel, its weight, and, consequently, how we can use it: for wrapping a sandwich. People’s understanding also includes how someone can use it for myriad other opportunities it affords, such as scrunching it into a ball for a game of hoops, or covering one’s hair.
All of these uses arise because of the nature of human bodies and needs: People have hands that can fold paper, a head of hair that is about the same size as a sandwich wrapper, and a need to be employed and thus follow rules like covering hair. That is, people understand how to make use of stuff in ways that are
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