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In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.
For example, oxygen is necessary for fire. But one cannot assume that everywhere there is oxygen, there is fire. A condition X is sufficient for Y if X, by itself, is enough to bring about Y. For example, riding the bus is a sufficient mode of transportation to get to work.
Some examples of these include, "uh huh," "yeah," "really," and head nods that act as continuers. They are used to signal that a phrase has been understood and that the conversation can move on. Relevant next turn refers to the initiation or invitation to respond between speakers, including verbal and nonverbal prompts for turn-taking in ...
Some researchers include a metacognitive component in their definition. In this view, the Dunning–Kruger effect is the thesis that those who are incompetent in a given area tend to be ignorant of their incompetence, i.e., they lack the metacognitive ability to become aware of their incompetence.
The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.
Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...
One example of a global ambiguity is "The woman held the baby in the green blanket." In this example, the baby, incidentally wrapped in the green blanket, is being held by the woman, or the woman is using the green blanket as an instrument to hold the baby, or the woman is wrapped in the green blanket and holding the baby.
According to one user, who had access to a private early release of the OpenAI GPT-3 API, GPT-3 was "eerily good" at writing "amazingly coherent text" with only a few simple prompts. [20] In an initial experiment 80 US subjects were asked to judge if short ~200 word articles were written by humans or GPT-3.