Tag: artificial intelligence

In part 2 of this series, we showed you how to use Amazon SageMaker Studio notebooks with natural language input to assist with threat hunting. This is done by using SageMaker Studio to automatically generate and run SQL queries on Amazon Athena with Amazon Bedrock and Amazon Security Lake. The Security Lake service team and […]

Amazon Web Services (AWS) is pleased to announce the release of new Security Reference Architecture (SRA) code examples for securing generative AI workloads. The examples include two comprehensive capabilities focusing on secure model inference and RAG implementations, covering a wide range of security best practices using AWS generative AI services. These new code examples are […]

English | German | French Around the world, organizations are evaluating and embracing artificial intelligence (AI) and machine learning (ML) to drive innovation and efficiency. From accelerating research and enhancing customer experiences to optimizing business processes, improving patient outcomes, and enriching public services, the transformative potential of AI is being realized across sectors. Although using […]

Retrieval-Augmented Generative (RAG) applications enhance the responses retrieved from large language models (LLMs) by integrating external data such as downloaded files, web scrapings, and user-contributed data pools. This integration improves the models’ performance by adding relevant context to the prompt. While RAG applications are a powerful way to dynamically add additional context to an LLM’s prompt […]

Mitigate risks like data exposure, model exploits, and ethical lapses when deploying Amazon Bedrock chatbots. Implement guardrails, encryption, access controls, and governance frameworks.

RSA Conference 2024 drew 650 speakers, 600 exhibitors, and thousands of security practitioners from across the globe to the Moscone Center in San Francisco, California from May 6 through 9. The keynote lineup was diverse, with 33 presentations featuring speakers ranging from WarGames actor Matthew Broderick, to public and private-sector luminaries such as Cybersecurity and Infrastructure Security […]

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 […]