A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.
The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.
Which solution will meet these requirements?
A company wants to implement a generative AI assistant to provide consistent responses to various phrasings of user questions.
Which advantages can generative AI provide in this use case?
A financial institution is building an AI solution to make loan approval decisions by using a foundation model (FM). For security and audit purposes, the company needs the AI solution ' s decisions to be explainable.
Which factor relates to the explainability of the AI solution ' s decisions?
Which AWS service makes foundation models (FMs) available to help users build and scale generative AI applications?
A student at a university is copying content from generative AI to write essays.
Which challenge of responsible generative AI does this scenario represent?
A company is training ML models on datasets. The datasets contain some classes that have more examples than other classes. The company wants to measure how well the model balances detecting and labeling the classes.
Which metric should the company use?
A company is using a pre-trained large language model (LLM) to extract information from documents. The company noticed that a newer LLM from a different provider is available on Amazon Bedrock. The company wants to transition to the new LLM on Amazon Bedrock.
What does the company need to do to transition to the new LLM?
A company is using a foundation model (FM) to generate creative marketing slogans for various products. The company wants to reuse a standard template with common instructions when generating slogans for different products. However, the company needs to add short descriptions for each product.
Which Amazon Bedrock solution will meet these requirements?
A financial company is building an ML model to classify fraudulent transactions based on customer data and transaction patterns. The company wants to evaluate the model’s performance. The company must ensure that the model makes correct predictions and minimizes false positives.
Which evaluation metric will meet these requirements?
