A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.
Which Amazon SageMaker inference option will meet these requirements?
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?
A company wants to create a chatbot that answers questions about human resources policies. The company is using a large language model (LLM) and has a large digital documentation base.
Which technique should the company use to optimize the generated responses?
A company wants to develop an Al application to help its employees check open customer claims, identify details for a specific claim, and access documents for a claim. Which solution meets these requirements?
Which option is an example of unsupervised learning?
A company needs to build its own large language model (LLM) based on only the company's private data. The company is concerned about the environmental effect of the training process.
Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?
An animation company wants to provide subtitles for its content. Which AWS service meets this requirement?
A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.
Which solution will meet this requirement?
A company has a generative AI application that uses a pre-trained foundation model (FM) on Amazon Bedrock. The company wants the FM to include more context by using company information.
Which solution meets these requirements MOST cost-effectively?
A company wants to create an application to summarize meetings by using meeting audio recordings.
Select and order the correct steps from the following list to create the application. Each step should be selected one time or not at all. (Select and order THREE.)
• Convert meeting audio recordings to meeting text files by using Amazon Polly.
• Convert meeting audio recordings to meeting text files by using Amazon Transcribe.
• Store meeting audio recordings in an Amazon S3 bucket.
• Store meeting audio recordings in an Amazon Elastic Block Store (Amazon EBS) volume.
• Summarize meeting text files by using Amazon Bedrock.
• Summarize meeting text files by using Amazon Lex.
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