AWS SageMaker Clarify

Overview

AWS SageMaker Clarify is a component of Amazon SageMaker that provides integrated bias and drift detection capabilities for cloud-based machine learning models. It enables organizations to evaluate models and explain model predictions, with particular strength in assessing foundation models for generative AI applications.

Key Features

• Foundation Model Evaluation: Automatically evaluate foundation models for specific generative AI use cases with metrics including accuracy, robustness, and toxicity assessment
• Bias Detection: Integrated bias detection to identify and measure fairness issues in model predictions
• Drift Detection: Monitor and detect model drift to ensure continued performance over time
• Model Explainability: Generate explanations for model predictions to improve transparency and interpretability
• Cloud-Native Integration: Built into the AWS SageMaker ecosystem for seamless integration with other machine learning tools and workflows

Use Cases

• Generative AI Quality Assurance: Evaluate foundation models before deployment to production environments
• Regulatory Compliance: Assess models for bias and fairness to meet compliance requirements
• Model Monitoring: Continuously track model performance and detect degradation through drift detection
• Transparency & Governance: Explain model decisions to stakeholders, customers, and regulatory bodies
• Risk Mitigation: Identify potential issues with model predictions related to toxicity, accuracy, and robustness

Pricing & Access

Pricing Model: Usage-based (Pay-As-You-Go)

Users pay only for the resources consumed when running evaluations and monitoring tasks. AWS offers flexible pricing options including: