APIs Big data Government 
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
AUGUST 31, 2023
The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.
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AWS Machine Learning
DECEMBER 1, 2022
Overview of model governance. Model governance is a framework that gives systematic visibility into model development, validation, and usage. Model governance is applicable across the end-to-end ML workflow, starting from identifying the ML use case to ongoing monitoring of a deployed model through alerts, reports, and dashboards.
AWS Machine Learning
OCTOBER 29, 2024
This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. Configure centralized logging to API calls across multiple accounts using CloudTrail.
AWS Machine Learning
OCTOBER 23, 2024
Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. Its low-code interface drastically reduces the time needed to develop generative AI applications.
AWS Machine Learning
FEBRUARY 21, 2025
Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.
AWS Machine Learning
APRIL 30, 2025
Achieving scale, reliability, and compliance Factors to consider in transitioning to full-scale production include scalability, data governance, privacy, consistent and responsible AI behaviors, security, integration with existing systems, monitoring, end-user feedback collection, and business impact measurement.
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