Garbage in, garbage out” (often abbreviated as GIGO) is a classic phrase in computing and data science.
Meaning:
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If you feed a system (like a computer program, algorithm, or AI model) poor-quality input, you will get poor-quality output.
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In other words, the output is only as good as the input you provide.
Examples:
Prompt Engineering: If your prompt is not clear and detailed any LLM model will not give you the desired output of yours. At times LLM models gets Hallucinations.
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Data Analysis: If your dataset has errors or missing values, any analysis or predictions will be unreliable.
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Programming: If a user enters invalid data, the program might crash or give wrong results.
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AI / Prompt Engineering: If you give vague, confusing, or poorly structured prompts to an AI model, the responses will be low quality — which is why prompt engineering is so important.
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