Title: AWS re:Inforce 2024 - Build responsible AI applications with Guardrails for Amazon Bedrock (GRC325)

Insights:

• Introduction to Guardrails for Amazon Bedrock: The session focuses on building safe and responsible generative AI applications using guardrails for Amazon Bedrock. These guardrails help manage undesirable topics, toxicity, privacy, and bias in AI applications.
• Challenges in Generative AI: Generative AI applications face challenges such as avoiding controversial topics, preventing toxic content, protecting privacy, and mitigating bias. These challenges necessitate robust safeguards.
• Native Safeguards and Customization: While foundation models on Amazon Bedrock have built-in safeguards, they are rigid and may require additional customization to align with specific use cases and organizational policies.
• Guardrails Capabilities: Guardrails for Amazon Bedrock are foundation model agnostic and work with various developer tools. They allow configuration of policies to avoid certain topics, filter harmful content, prevent prompt injection and jailbreaking attacks, and manage sensitive information.
• Policy Types in Guardrails:
  • Denied Topics: Blocks specific topics like investment advice in an online banking assistant.
  • Content Filters: Filters harmful content across categories such as hate, insults, sexual violence, misconduct, and criminal activity.
  • Prompt Attack Filters: Detects and prevents prompt injection and jailbreaking attacks.
  • Sensitive Information Filters: Blocks or redacts personally identifiable information (PII) and other sensitive data.
  • Word Filters: Blocks custom words, including profanity and competitor names.
• Guardrails Implementation: Guardrails work by intercepting user input and foundation model responses, ensuring compliance with configured policies. Violations trigger pre-configured messages to maintain application safety.
• Demo Overview: The demo showcases the creation and testing of guardrails in an online banking assistant application, highlighting the configuration of content filters, denied topics, and prompt attack filters.
• Agent Integration: Demonstrates how guardrails integrate with Bedrock agents to execute multi-step actions while ensuring compliance with safety policies.
• Sensitive Information Redaction: Shows how sensitive information filters can redact PII in customer service applications, ensuring privacy and compliance.

Quotes:

• "Foundation models are incredibly powerful and they can do like a wide range of tasks and they can provide information about a variety of topics."
• "When you're building a generative AI application it brings a whole new set of challenges."
• "You might want to prevent and remove all toxic and harmful content that are getting generated within gen AI applications."
• "Guardrails are foundation model agnostic, as in they work with all foundation models, all text-based foundation models as of right now."
• "You can configure certain topics that you want to avoid using short natural language descriptions."
• "GuardRails work by intercepting the user input as well as the foundation model responses."
• "If any of the policy is in violation, a pre-configured approved message gets returned back to the end users ensuring the safety of the genii application."
• "You can configure filters to prevent prompt injection and jailbreaking attacks."
• "Sensitive information filter can help you out in getting the desired outcome there, and it's redacted throughout the whole response."