Unlocking Safer AI: Your Two-Part Field Guide

Large language models are transforming product development and simultaneously becoming targets for adversarial attacks. Sofia Jakovcevic, an AI Solutions Engineer at Arize AI, authored a two-part guide to assist teams in understanding and defending against these threats. The first part focuses on jailbreaks, providing insights from red-teaming experiences to help identify potential vulnerabilities such as system-prompt leaks and emotional manipulations, illustrated through live examples. The second part serves as a practical guide for implementing guardrails to safeguard AI systems, discussing various defensive strategies like keyword bans, ML-based detectors, and LLM moderation, highlighting the importance of observability, and offering resources like a GitHub repository for ongoing guardrail tuning. This comprehensive approach equips teams to anticipate and mitigate vulnerabilities, enabling them to deploy AI solutions securely and confidently.

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