AWS Machine Learning

FEBRUARY 21, 2025

The solution uses the FMs tool use capabilities, accessed through the Amazon Bedrock Converse API. This enables the FMs to not just process text, but to actively engage with various external tools and APIs to perform complex document analysis tasks. For more details on how tool use works, refer to The complete tool use workflow.

APIs 95

APIs Healthcare Consulting Consulting 95

AWS Machine Learning

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Government 132

Government APIs Enterprise Best practices 132

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.

Government 70

Government Engineering Enterprise APIs 70

AWS Machine Learning

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. All these capabilities are built to help multiple lines of business innovate with speed and agility while governing at scale with central controls.

Healthcare 128

Healthcare Government Engineering APIs 128

AWS Machine Learning

APRIL 18, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts 133

Scripts Best practices Engineering Accountability 133

AWS Machine Learning

NOVEMBER 22, 2023

Also learn how prompts can be integrated with your architecture and how to use API parameters for tuning the model parameters using Amazon Bedrock. This chalk talk provides an introduction to best practices for risk assessment related to fairness, robustness, explainability, privacy and security, transparency, and governance.

Engineering 139

Engineering Best practices APIs Government 139

AWS Machine Learning

MARCH 14, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon via a single API. This improves efficiency and allows larger contexts to be used. This supports safer adoption.

Best practices 137

Best practices Engineering Chatbots Enterprise 137