Prompt engineering: Difference between revisions

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==Introduction==
==Introduction==
[[Prompt engineering]] is an emerging research area within Human-Computer Interaction (HCI) that involves the formal search for [[prompts]] to produce desired outcomes from [[AI models]]. This process involves selecting and composing sentences to achieve a certain result, such as a specific visual style in [[text-to-image models]] or a different tone in the response of a [[text-to-text]] one. Unlike the hard sciences of STEM fields, this is an evolving technique based on trial and error to produce effective AI outcomes. <ref name="”1”">Bouchard, L (2022). Prompting eExplained: How to Talk to ChatGPT. Louis Bouchard. https://www.louisbouchard.ai/prompting-explained/</ref> <ref name="”2”">Oppenlaender, J (2022). A Taxonomy of Prompt Modifiers for Text-To-Image Generation. arXiv:2204.13988v2</ref> <ref name="”3”">Liu, V and Chilton, LB (2021). Design Guidelines for Prompt Engineering Text-to-Image Generative Models. arXiv:2109.06977v2</ref> Prompt engineers serve as translators between "human language" and "AI language," transforming an idea into words that the AI model can comprehend. <ref name="”1”"></ref>
[[Prompt engineering]] is an emerging research area within Human-Computer Interaction (HCI) that involves the formal search for [[prompts]] to produce desired outcomes from [[AI models]]. This process involves selecting and composing sentences to achieve a certain result, such as a specific visual style in [[text-to-image models]] or a different tone in the response of a [[text-to-text models|text-to-text one]]. Unlike the hard sciences of STEM fields, this is an evolving technique based on trial and error to produce effective AI outcomes. <ref name="”1”">Bouchard, L (2022). Prompting eExplained: How to Talk to ChatGPT. Louis Bouchard. https://www.louisbouchard.ai/prompting-explained/</ref> <ref name="”2”">Oppenlaender, J (2022). A Taxonomy of Prompt Modifiers for Text-To-Image Generation. arXiv:2204.13988v2</ref> <ref name="”3”">Liu, V and Chilton, LB (2021). Design Guidelines for Prompt Engineering Text-to-Image Generative Models. arXiv:2109.06977v2</ref> Prompt engineers serve as translators between "human language" and "AI language," transforming an idea into words that the AI model can comprehend. <ref name="”1”"></ref>


The process of prompt engineering is similar to a conversation with the generative system, with practitioners adapting and refining prompts to improve outcomes. <ref name="”2”"></ref> It has emerged as a new form of interaction with models that have learned complex abstractions from consuming large amounts of data from the internet. These models have metalearning capabilities and can adapt their abstractions on the fly to fit new tasks, making it necessary to prompt them with specific knowledge and abstractions to perform well on new tasks. The term "prompt engineering" was coined by Gwern (writer and technologist), who evaluated GPT3's capabilities on creative fiction and suggested that a new course of interaction would be to figure out how to prompt the model to elicit specific knowledge and abstractions. <ref name="”3”"></ref>
The process of prompt engineering is similar to a conversation with the [[generative system]], with practitioners adapting and refining prompts to improve outcomes. <ref name="”2”"></ref> It has emerged as a new form of interaction with models that have learned complex abstractions from consuming large amounts of data from the internet. These models have metalearning capabilities and can adapt their abstractions on the fly to fit new tasks, making it necessary to prompt them with specific knowledge and abstractions to perform well on new tasks. The term "prompt engineering" was coined by [[Gwern]] (writer and technologist), who evaluated GPT3's capabilities on creative fiction and suggested that a new course of interaction would be to figure out how to prompt the model to elicit specific knowledge and abstractions. <ref name="”3”"></ref>


In order to get the best results from these large and powerful generative models, prompt engineering is a critical skill that users must possess. Adding certain keywords and phrases to the textual input prompts known as "prompt modifiers" can improve the aesthetic qualities and subjective attractiveness of the generated images, for example. The process of prompt engineering is iterative and experimental in nature, where practitioners formulate prompts as probes into the generative models' latent space. There are various resources and guides available to novices to help them write effective input prompts for text-to-image generation systems, however, prompt engineering is still an emerging practice that requires extensive experimentation and trial and error. <ref name="”1”"></ref><ref name="”2”"></ref><ref name="”3”"></ref>
In order to get the best results from these large and powerful generative models, prompt engineering is a critical skill that users must possess. Adding certain keywords and phrases to the textual input prompts known as "[[prompt modifiers]]" can improve the aesthetic qualities and subjective attractiveness of the [[generated images]], for example. The process of prompt engineering is iterative and experimental in nature, where practitioners formulate prompts as probes into the generative models' latent space. There are various resources and guides available to novices to help them write effective input prompts for [[text-to-image generation]] systems, however, prompt engineering is still an emerging practice that requires extensive experimentation and trial and error. <ref name="”1”"></ref><ref name="”2”"></ref><ref name="”3”"></ref>


Manual prompt engineering is laborious, it may be infeasible in some situations, and the prompt results may vary between various model versions. <ref name="”4”">Hao, Y, Chi, Z, Dong, L and Wei, F (2022). Optimizing Prompts for Text-to-Image Generation. arXiv:2212.09611v1</ref> However, there have been developments in automated prompt generation which rephrases the input, making it more model-friendly. <ref name="”5”">Ana, B (2022). Design your AI Art Generator Prompt Using ChatGPT. Towards AI. https://pub.towardsai.net/design-your-ai-art-generator-prompt-using-chatgpt-7a3dfddf6f76</ref>
Manual prompt engineering is laborious, it may be infeasible in some situations, and the prompt results may vary between various model versions. <ref name="”4”">Hao, Y, Chi, Z, Dong, L and Wei, F (2022). Optimizing Prompts for Text-to-Image Generation. arXiv:2212.09611v1</ref> However, there have been developments in automated [[prompt generation]] which rephrases the input, making it more model-friendly. <ref name="”5”">Ana, B (2022). Design your AI Art Generator Prompt Using ChatGPT. Towards AI. https://pub.towardsai.net/design-your-ai-art-generator-prompt-using-chatgpt-7a3dfddf6f76</ref>


Therefore, this field is important for the generation of high-quality AI-generated outputs. Text-to-image models, in particular, face limitations in their text encoders, making prompt design even more crucial to produce aesthetically pleasing images with current models. <ref name="”4”"></ref> These models work based on caption matching techniques and are pre-trained using millions of text-image datasets. While a result will be generated for any prompt, the quality of the artwork is directly proportional to the quality of the prompt. <ref name="”6”">Raj, G (2022). How to Write Good Prompts for AI Art Generators: Prompt Engineering Made Easy. Decentralized Creator. https://decentralizedcreator.com/write-good-prompts-for-ai-art-generators/</ref>
Therefore, this field is important for the generation of high-quality [[AI-generated outputs]]. [[Text-to-image models]], in particular, face limitations in their text encoders, making prompt design even more crucial to produce aesthetically pleasing images with current models. <ref name="”4”"></ref> These models work based on caption matching techniques and are pre-trained using millions of [[text-image datasets]]. While a result will be generated for any prompt, the quality of the artwork is directly proportional to the quality of the prompt. <ref name="”6”">Raj, G (2022). How to Write Good Prompts for AI Art Generators: Prompt Engineering Made Easy. Decentralized Creator. https://decentralizedcreator.com/write-good-prompts-for-ai-art-generators/</ref>


===Basic prompt structure===
===Basic prompt structure===