<ul data-eligibleForWebStory="true"><li>Prompt engineering guides a model's output by adjusting inputs, enhancing performance.</li><li>For common topics and widespread knowledge, such as from large training datasets, prompt</li><li>engineering may suffice. For specialized domains, recent data, or proprietary info, consider fine-tuning.</li><li>Fine-tuning alters a model's internal weights for specific language patterns, yielding accuracy.</li><li>Fine-tuning, though resource-intensive, can be more efficient for domain-specific applications at scale.</li></ul>

Prompt Engineering or Fine-Tuning: Which Is Best for Your AI Project?

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