Generative artificial intelligence (GenAI) technology is changing the way businesses operate. GenAI is now being used for every possible task, possibly even trending towards industrialisation. The most important activity in implementing GenAI is to develop and train models to generate the meaningful information needed by humans or systems. The process of feeding the information to generate responses is called prompt engineering.
In simple terms, prompt engineering is the process of creating effective prompts that enable GenAI models to generate responses based on given inputs. It is the art of asking the right question to get better output from a GenAI model. These GenAI models are called large language models (LLMs). They can be programmed in English as well as other languages.
Prompts are pieces of text that are used to provide context and guidance to GenAI models. These prompts learn from diverse input data, minimise biases, and provide additional guidance to the model to generate accurate output. A knowledgeable prompt generates highquality AI content related to images, code, text, or data summaries.
Key components of prompt engineering
The key components of prompt formation include instruction, context, input data and output.
Instruction: We must write clear instructions to the model for completing the task. The instruction:
Establishes the goal of the model
Creates text that is being processed or transformed by the model
Can be simple or complex
Context: Important details or context must be provided to get more relevant answers. The context:
Provides details that help the model to answer
Assists the model with necessary information style and tone
Input data: Actual data that the model will be using is referred to as input data.
Express query as clearly as possible
This story is from the March 2024 edition of Open Source For You.
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This story is from the March 2024 edition of Open Source For You.
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