What is AI Prompt Engineering?
AI prompt engineering is the process of crafting prompts to guide an AI language model like ChatGPT in a desired direction or to achieve a certain output. While the AI model learns to generate text from a large corpus of human language, there can be significant variability in its output. The purpose of prompt engineering is to minimize this variability and guide the AI towards generating the desired response.
The nature of a prompt can significantly influence the response of the AI model. This includes factors like the length of the prompt, the specificity of the prompt, the use of certain keywords or tags, and more. It is an iterative process that requires a deep understanding of how the AI model responds to different types of prompts.
What are some AI Prompt Engineering techniques?
To improve results use these techniques when formulating prompts.
Ratios and Weights: In some AI models, you can use ratios and weights to adjust the importance of different parts of the input. For instance, you might assign a higher weight to a certain keyword or tag to make it more influential in the AI’s output. This is not explicitly possible with GPT-3 or GPT-4 based models, as they don’t offer an interface for this kind of prompt manipulation directly. But, you can achieve a similar effect by repeating or emphasizing certain parts of the prompt.
Example: You might prompt the model with: “Describe a day at the beach. Remember, I want to hear a lot about the sand and the waves. The sand and the waves are the most important parts.”
Tags and Keywords: Using specific keywords or tags can guide the model towards a specific topic or type of response.
Example: “Write a [poem] about [love] and [autumn]”. The model is more likely to generate a poem involving the themes of love and autumn.
Brackets or Braces for Emphasis: This approach is more experimental but it involves the use of brackets or braces to emphasize a certain part of the prompt. Again, it’s not clear if this actually works or if the AI model treats these brackets or braces as normal text.
Example: “Tell me about the {American Civil War}”. It’s unclear if this is more effective than simply “Tell me about the American Civil War.”
Negative Prompts: These are prompts that tell the model what not to do. This could be used to avoid certain topics or types of responses.
Example: “Write a story about a vacation, but don’t mention anything about airplanes.”
Remember, the effectiveness of these techniques can vary. AI models are complex and it’s often not clear how they will respond to a specific prompt. This makes prompt engineering more of an art than a science, requiring a process of trial and error to find the most effective prompts.
