Databricks Generative AI Engineer Associate Question 151
Single answerYou are tasked with developing a chatbot for a financial services company that requires accurate and contextually relevant responses to customer queries about loan options and interest rates. The application must prioritize domain-specific knowledge, high accuracy, and the ability to fine-tune the model to incorporate proprietary financial data. Which type of LLM would be the most appropriate choice for this application?
- A
A general-purpose LLM without fine-tuning capabilities
- B
A domain-specific LLM pre-trained on financial data with fine-tuning capabilities
- C
An open-source general-purpose LLM with limited training on financial data
- D
A lightweight LLM optimized for real-time responses but lacking fine-tuning capabilities
Show answer and explanation
Correct answer: B
Explanation
For an application that requires domain-specific knowledge, high accuracy, and the ability to incorporate proprietary data, a domain-specific LLM with fine-tuning capabilities is the most suitable choice. This ensures that the chatbot can provide accurate, contextually relevant, and customized responses, meeting the needs of the financial services company.
- A. Incorrect.
A general-purpose LLM without fine-tuning capabilities may provide general answers but lacks the ability to incorporate proprietary financial data, which is essential for the application's requirements.
- B. Correct.
A domain-specific LLM pre-trained on financial data with fine-tuning capabilities is the best choice since it combines specialized knowledge with the ability to adapt to the company's proprietary data, ensuring accuracy and contextual relevance.
- C. Incorrect.
An open-source general-purpose LLM with limited training on financial data might not have sufficient domain knowledge or the ability to fine-tune effectively, leading to suboptimal performance for the application's needs.
- D. Incorrect.
A lightweight LLM optimized for real-time responses may be fast but lacks the domain-specific knowledge and fine-tuning capabilities required for this use case.