Topic 1 Question 64
A research company implemented a chatbot by using a foundation model (FM) from Amazon Bedrock. The chatbot searches for answers to questions from a large database of research papers. After multiple prompt engineering attempts, the company notices that the FM is performing poorly because of the complex scientific terms in the research papers. How can the company improve the performance of the chatbot?
Use few-shot prompting to define how the FM can answer the questions.
Use domain adaptation fine-tuning to adapt the FM to complex scientific terms.
Change the FM inference parameters.
Clean the research paper data to remove complex scientific terms.
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コメント(7)
- 正解だと思う選択肢: B
Domain adaptation fine-tuning allows you to fine-tune the foundation model (FM) on a dataset that includes examples of the specific domain, in this case, scientific papers with complex terms. This way, the model can better understand and handle the specialized terminology, improving its accuracy when answering domain-specific questions.
👍 3jove2024/11/09 - 正解だと思う選択肢: B
B. “After multiple prompt engineering attempts” means few-shot prompt has tried or? So A is not the correct one.
👍 2CTao2024/11/30 - 正解だと思う選択肢: A
A is correct
👍 1PHD_CHENG2024/11/26
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