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A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [3] providing relevant context, or describing a character for the AI to mimic. [1]
The goal of response prompting is to transfer stimulus control from the prompt to the desired discriminative stimulus. [1] Several response prompting procedures are commonly used in special education research: (a) system of least prompts, (b) most to least prompting, (c) progressive and constant time delay, and (d) simultaneous prompting.
Prompt injection can be viewed as a code injection attack using adversarial prompt engineering. In 2022, the NCC Group characterized prompt injection as a new class of vulnerability of AI/ML systems. [10] The concept of prompt injection was first discovered by Jonathan Cefalu from Preamble in May 2022 in a letter to OpenAI who called it command ...
Few-shot learning and one-shot learning may refer to: Few-shot learning, a form of prompt engineering in generative AI; One-shot learning (computer vision)
The name is a play on words based on the earlier concept of one-shot learning, in which classification can be learned from only one, or a few, examples. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. [1]
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The word "TelePrompTer", with internal capitalization, originated as a trade name used by the TelePrompTer Corporation, which first developed the device in the 1950s. The word "teleprompter", with no capitalization, has become a genericized trademark, because it is used to refer to similar systems manufactured by many different companies. Some ...
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