Not getting the response you want from a generative AI model? You might be dealing with AI hallucination, a problem that occurs when the model produces inaccurate or irrelevant outputs.
It is caused by various factors, such as the quality of the data used to train the model, a lack of context, or the ambiguity of the prompt. Fortunately, there are techniques you can use to get more reliable output from an AI model.
1. Provide Clear and Specific Prompts
The first step in minimizing AI hallucination is to create clear and highly specific prompts. Vague or ambiguous prompts can lead to unpredictable results, as AI models may attempt to interpret the intent behind the prompt. Instead, be explicit in your instructions.
Instead of asking, “Tell me about dogs,” you could prompt, “Give me a detailed description of the physical characteristics and temperament of Golden Retrievers.” Refining your prompt until it’s clear is an easy way to prevent AI hallucination.