Category: Amazon Bedrock

Generative artificial intelligence (AI) has captured the imagination of organizations and individuals around the world, and many have already adopted it to help improve workforce productivity, transform customer experiences, and more. When you use a generative AI-based service, you should understand how the information that you enter into the application is stored, processed, shared, and […]

This is part 3 of a series of posts on securing generative AI. We recommend starting with the overview post Securing generative AI: An introduction to the Generative AI Security Scoping Matrix, which introduces the scoping matrix detailed in this post. This post discusses the considerations when implementing security controls to protect a generative AI […]

In part 1, we discussed how to use Amazon SageMaker Studio to analyze time-series data in Amazon Security Lake to identify critical areas and prioritize efforts to help increase your security posture. Security Lake provides additional visibility into your environment by consolidating and normalizing security data from both AWS and non-AWS sources. Security teams can […]

Generative artificial intelligence (generative AI) has captured the imagination of organizations and is transforming the customer experience in industries of every size across the globe. This leap in AI capability, fueled by multi-billion-parameter large language models (LLMs) and transformer neural networks, has opened the door to new productivity improvements, creative capabilities, and more. As organizations […]