by Michele Laurelli
The practice of designing effective text prompts to guide large language models toward desired outputs.
Prompt engineering involves crafting instructions, examples, and context to optimize LLM performance. Techniques include few-shot prompting, chain-of-thought, and role-playing.
Few-shot prompting with examples
Chain-of-thought for reasoning
System prompts for chatbot behavior
A neural network with billions of parameters trained on massive text datasets to understand and generate human language.
A family of large language models developed by OpenAI that use transformer architecture for text generation.
A model's ability to perform tasks it wasn't explicitly trained on, using only task descriptions or examples.