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Specialized prompts
Recent studies have shown that prompt-based AI techniques can be very effective in certain domains. For example, large-scale language models such as OpenAI’s GPT-4 can be utilized in a variety of fields based on general knowledge, but sometimes they lack deep understanding of a specific domain. To compensate for this, the method of fine-tuning the model has traditionally been used. However, a recent study found that GPT-4 performed better in the medical field when used simply through prompt engineering without fine-tuning. This suggests that prompt strategies can be very effective in eliciting expert knowledge in foundation models.
This is a good example of how prompting, which costs very little compared to fine tuning, can push the performance of a specific model to its limit, and these research results suggest that prompt-based AI technology can be used as a powerful tool in various fields including medicine. This provides new possibilities for experts in the field along with the development of AI technology, and suggests an important development direction for future research and applications.
What to do to create a specialized prompt
Context: Prompts should include clear context and target. This gives the AI direction to work on, and helps it get more accurate and relevant results. For example, when asking for information on a specific topic, explaining the background or context can help the AI give a more accurate answer.
Repeated testing and adjustments: AI doesn’t always give perfect results on the first try, so it’s important to try multiple times and adjust prompts as needed. This will help AI gradually improve its responses.
Experiment with different versions: Try different ways to phrase your prompts to see which format works best for you. This will help you understand how your AI responds and find the best way to ask questions.
Clearly communicate user intent: AI cannot directly recognize the user’s intent behind the prompt. Therefore, it is important to clearly communicate the user’s intent. By clearly presenting specific examples or requirements, AI can respond more accurately.
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