A company is building a contact center application and wants to gain insights from customer conversations. The company wants to analyze and extract key information from the audio of the customer calls. Which solution meets these requirements?
A. Build a conversational chatbot by using Amazon Lex.
B. Transcribe call recordings by using Amazon Transcribe.
C. Extract information from call recordings by using Amazon SageMaker Model Monitor.
D. Create classification labels by using Amazon Comprehend.
正解を表示
正解
B
問題 17
Question#17Topic1
A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products. Which methodology should the company use to meet these requirements?
A. Supervised learning
B. Unsupervised learning
C. Reinforcement learning
D. Reinforcement learning from human feedback (RLHF)
正解を表示
正解
B
問題 18
Question#18Topic1
An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images. Which type of FM should the AI practitioner use to power the search application?
A. Multi-modal embedding model
B. Text embedding model
C. Multi-modal generation model
D. Image generation model
正解を表示
正解
A
問題 19
Question#19Topic1
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will successfully fine-tune the model?
A. Provide labeled data with the prompt field and the completion field.
B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
C. Purchase Provisioned Throughput for Amazon Bedrock.
D. Train the model on journals and textbooks.
正解を表示
正解
A
問題 20
Question#20Topic1
A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source. Which solution meets these requirements?
A. Build a speech recognition system.
B. Create a natural language processing (NLP) named entity recognition system.