APIs Government Metrics 
AWS Machine Learning
NOVEMBER 14, 2024
Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. This streamlines the ML workflows, enables better visibility and governance, and accelerates the adoption of ML models across the organization.
AWS Machine Learning
MARCH 25, 2025
Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Building generative AI applications requires more than model API calls.
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AWS Machine Learning
NOVEMBER 13, 2024
You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.
AWS Machine Learning
NOVEMBER 7, 2024
We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic.
AWS Machine Learning
NOVEMBER 15, 2024
For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. Regular evaluations allow you to adjust and steer the AI’s behavior based on feedback and performance metrics.
AWS Machine Learning
MAY 30, 2025
In reality, its a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG) and workflows involving agents. This approach facilitates centralized governance and operations.
AWS Machine Learning
JANUARY 28, 2025
Evaluation algorithm Computes evaluation metrics to model outputs. Different algorithms have different metrics to be specified. It functions as a standalone HTTP server that provides various REST API endpoints for monitoring, recording, and visualizing experiment runs. This allows you to keep track of your ML experiments.
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