Aranya, Research Economist, Dohatec Research Team, presented on prompt engineering on Monday, March 20, 2023. The goal of the presentation was to familiarize the new employees of the Gulshan 2 (3rd floor) office with the concept of Prompt engineering and show them how it can be used in combination with the newest technology, Chat GPT.
Prompt engineering is a natural language processing (NLP) process that involves designing and optimizing prompts for machine learning models, especially those that use language models such as GPT-3.
A prompt in NLP is a piece of text that is given to a machine learning model to help it generate a reaction or output. Prompt engineering entails designing cues in such a way that the model’s output is as accurate and relevant as possible.
Defining the job or issue to be solved, identifying the relevant input data, designing the prompt structure, selecting appropriate keywords, and optimizing the prompt based on model performance are all steps in the prompt engineering process.
Understanding the strengths and weaknesses of the machine learning model being used, and adjusting the prompts accordingly, is an essential aspect of prompt engineering. Experimenting with various prompt structures, varying the length and complexity of the prompt, and using different kinds of keywords or context to guide the model’s output are all examples of this.
Prompt engineering is especially critical for applications requiring high precision and relevance, such as chatbots, question-answering systems, and language translation. Machine learning models can be trained to produce more accurate and relevant responses by meticulously crafting prompts, thereby improving the overall quality of NLP applications.