Topic 1 Question 75
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy. Which additional data does the company need to meet these requirements?
Pairs of chatbot responses and correct user intents
Pairs of user messages and correct chatbot responses
Pairs of user messages and correct user intents
Pairs of user intents and correct chatbot responses
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- 正解だと思う選択肢: C
C is correct answer
👍 3PHD_CHENG2024/11/19 - 正解だと思う選択肢: C
C. Pairs of user messages and correct user intents
Explanation: Few-shot learning involves training a model with a small number of examples (or samples). In this case, the goal is to improve intent detection, which requires a clear understanding of the user's intent based on their message. To fine-tune the large language model (LLM) using few-shot learning, the model needs examples of user messages along with their corresponding correct user intents. These pairs will teach the model how to accurately classify user intents based on input messages.
👍 1aws_Tamilan2024/12/27 - 正解だと思う選択肢: C
C. Pairs of user messages and correct user intents Few-shot learning is a machine learning technique that allows the model to learn from small amounts of data, including labeled examples or "shots." In this case, the company wants to use few-shot learning to improve intent detection accuracy. To implement few-shot learning for intent detection, the company needs additional data in the form of pairs of user messages and their corresponding correct user intents. This data will serve as the "shooting" examples that the LLM can learn from.
👍 1AzureDP9002025/01/25
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