Your company is developing a LLM chatbot for customer support to answer complex queries. The developers aim to use rapid application development (RAD) for swift iterations and deployment. Which approach would be more aligned with RAD?

Question

Your company is developing a LLM chatbot for customer support to answer complex queries. The developers aim to use rapid application development (RAD) for  swift  iterations and deployment. Which approach would be more aligned with RAD?

Answer

Develop a custom LLM from scratch with domain-specific capabilities.

Answer

Implement a fine-tuning approach by training the LLM on a large dataset of company documents, then deploy the chatbot.

Answer

Use prompt engineering to customize responses, and continuously refine the prompts based on real-world feedback to improve the LLM’s performance.

Answer

Pre-process and structure all possible customer queries, mapping them to specific responses before training the model.

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