Remove APIs Remove Best practices Remove industry standards
article thumbnail

Security best practices to consider while fine-tuning models in Amazon Bedrock

AWS Machine Learning

In this post, we delve into the essential security best practices that organizations should consider when fine-tuning generative AI models. Implementing these procedures allows you to follow security best practices when you deploy and use your fine-tuned model within Amazon Bedrock for inference tasks. Choose Apply.

article thumbnail

Best practices to build generative AI applications on AWS

AWS Machine Learning

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 is because such tasks require organization-specific data and workflows that typically need custom programming.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

Because this is an emerging area, best practices, practical guidance, and design patterns are difficult to find in an easily consumable basis. This integration makes sure enterprises can take advantage of the full power of generative AI while adhering to best practices in operational excellence.

article thumbnail

Insights in implementing production-ready solutions with generative AI

AWS Machine Learning

Standard development best practices and effective cloud operating models, like AWS Well-Architected and the AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI , are key to enabling teams to spend most of their time on tasks with high business value, rather than on recurrent, manual operations.

article thumbnail

Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The AWS Well-Architected Framework provides best practices and guidelines for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. It calls the CreateDataSource and DeleteDataSource APIs. Minimally, you must specify the following properties: Name – Specify a name for the knowledge base.

APIs 128
article thumbnail

Using Agents for Amazon Bedrock to interactively generate infrastructure as code

AWS Machine Learning

This solution uses Retrieval Augmented Generation (RAG) to ensure the generated scripts adhere to organizational needs and industry standards. In this blog post, we explore how Agents for Amazon Bedrock can be used to generate customized, organization standards-compliant IaC scripts directly from uploaded architecture diagrams.

Scripts 138
article thumbnail

Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

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 131