A financial company wants to build workflows for human review of ML predictions. The company wants to define confidence thresholds for its use case and adjust the thresholds over time.Which AWS service meets these requirements?
Answer(s): B
Amazon Augmented AI (Amazon A2I) enables you to build workflows for human review of machine learning predictions, allowing you to define and adjust confidence thresholds for when human intervention is required.
HOTSPOT (Drag and Drop is not supported)Select and order the steps from the following list to correctly describe the ML lifecycle for a new custom model.Select each step one time.Hot Area:
Answer(s): A
HOTSPOT (Drag and Drop is not supported)A company wants to customize a foundation model (FM). The company wants to understand the customization methods and data types that are available.Select the correct customization method from the following list for each description. Select each customization method one time.Hot Area:
Fine-tuning uses labeled data to adapt a foundation model for improved performance on specific tasks.Continued pre-training uses large volumes of unlabeled domain-specific data to adapt a foundation model to a specific domain.Distillation transfers knowledge from a larger, more capable model into a smaller model while retaining performance characteristics.
A company needs to classify equipment types from images. The company has text descriptions and sample images for each equipment type.Which solution will meet these requirements with the LEAST operational overhead?
A multimodal foundation model in Amazon Bedrock can analyze images together with text instructions or descriptions, allowing the company to classify equipment without training, fine-tuning, or managing a separate machine learning model. This provides the required image understanding capability with the least operational overhead.
A company is building a customer service chatbot. The company wants the chatbot to improve its responses by learning from past interactions and online resources.Which AI learning strategy provides this self-improvement capability?
Reinforcement learning allows the chatbot to learn from interactions by receiving rewards for positive customer feedback, which helps the model self-improve over time. The other options do not directly provide a mechanism for continuous self-improvement based on interactions.
A financial services company must ensure that its generative AI-powered chatbot provides factual responses for regulatory compliance.Which solution prevents the underlying foundation model (FM) from hallucinating?
Amazon Bedrock Guardrails allows you to define rules and policies that evaluate and constrain both user inputs and model responses. By configuring guardrails, you can prevent the generative AI model from producing hallucinated or non-factual outputs, ensuring the chatbot adheres to compliance requirements and provides factual responses. This directly addresses the need to control hallucinations in generative AI systems for regulatory compliance.
A company uses Amazon SageMaker AI to generate article summaries in multiple languages. The company needs a metric to evaluate the quality of the summary translations in multiple languages.Which evaluation metric will meet these requirements?
Bilingual Evaluation Understudy measures how closely a generated translation matches one or more high-quality reference translations, making it well suited for evaluating the quality of multilingual summary translations.
A company has installed a security camera. The company uses an ML model to evaluate the security camera footage for potential thefts. The company has discovered that the model disproportionately flags people who are members of a specific ethnic group.Which type of bias is affecting the model output?
Sampling bias occurs when the training data is not representative of the overall population, leading to disproportionate flagging of specific groups. In this case, the model may have been trained on biased data that did not adequately represent all ethnic groups, resulting in skewed predictions. The other types of bias do not directly apply to the selection of training data or its representativeness.
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