In the rapid growth of generative AI, ensuring security and accuracy is crucial. Amazon BedRock’s Guardrail service offers powerful tools to detect and prevent false messages (hallucinations) when using custom or third-party models (FMs), ensuring data privacy and compliance. This article will guide you on ensuring safety and compliance with generative AI.
Table of Contents
Table of Contents
Amazon BedRock Guardrail Added Two New Safeguards
Amazon Bedrock’s Guardrail offers top-tier security features, allowing customers to implement safety measures based on application needs and internal AI governance rules. Its primary function is to help enterprises filter harmful content, block prompt attacks, and remove privacy-related information.”
Amazon BedRock Guardrail adds extra filtering layers to the model’s native capabilities, blocking up to 85% of harmful content and filtering over 75% of false responses in RAG and summarization tasks. It’s interesting how AWS uses Guardrail to help enterprises filter information.
Filtering Content
Content filters on AWS allow enterprises to set thresholds to block inappropriate content like hate speech, insults, and violence. These filters automatically detect and block restricted content in user inputs and model responses, ensuring generated responses are appropriate. For example, an AI customer service assistant can be designed to avoid offensive language.
Masking Sensitive Information
Guardrail protects user privacy by detecting and masking personally identifiable information (PII). Enterprises can use predefined or custom PII types to manage sensitive content in inputs and responses. For instance, a customer management center can mask personal information in service report summaries to ensure security compliance.
Combating False Information: Guardrail Enhances Accuracy in Generative AI
Generative AI often struggles with false information (hallucinations). Amazon Bedrock’s Guardrail uses contextual checks to filter and verify the accuracy of responses in RAG, summarization, and dialogues. For example, businesses can use Bedrock’s knowledge base to ensure reliable RAG applications by filtering out incorrect responses and validating them against their database.
Amazon Bedrock allows you to customize safeguards against false information with Guardrail, tailoring security and privacy measures to your needs. These measures can be applied to all Amazon Bedrock LLMs and custom models, and integrated with Agents and knowledge bases.
As generative AI grows, cybersecurity becomes vital. Forrester reports that 67% of enterprises using generative AI overlook cybersecurity risks. Bohon Cloud provides not only AI solutions but also robust cybersecurity support to ensure safe and secure application of new technologies.
