Prompt priming is a technique for improving the performance of AI language models (LLMs) by providing them with additional information or context before they generate text.
- Provide LLMs additional information/context in a prompt - LLM generate a response - User provides feedback on the response - LLM improve its response.
- Improve the relevance of the generated text - Increase the coherence of the generated text - Enhance the creativity of generated text - Personalize content etc.
- It is a way to provide AI language models with additional information or context - Generating creative text - Summarizing text clearly and concisely, etc.
- It is critical factor in influencing AI-generated responses. - Provide LLMs information needed to generate text relevant, coherent, & creative.
- When human communicate often provide context/hints to help others understand. - Similarly Use keywords/phrases & provide examples for LLM
- Explicit Prompt Priming - Implicit Prompt Priming - Creative Prompt Priming - Reinforcement priming
- Keyword-based Priming - Style and Tone Priming - Contextual Priming - Example-driven Priming
- Choose the right prompt - Use the right amount of priming - Experiment with different priming technique
- Difficult to find the right prompt for a particular task. - Time consuming to experiment - Sometimes lead to nonsensical or irrelevant responses.
- Prompt priming is a rapidly developing field, and improve the performance of AI models. - In future, it will create forms of art, entertainment, & powering self-driving cars.
- Prompt priming is a powerful technique used to improve the performance of AI models. - By choosing the right prompt, in right amount of priming, AI model performance can be significantly improved