Output Validation Strategies
Donato emphasizes the importance of not solely relying on LLMs for decision-making, advocating for thorough checks on inputs and outputs to ensure reliability. Daniel highlights the rapid development of tools for output validation, including traditional NLP models that can effectively detect harmful content and verify factual consistency. Together, they explore how these strategies can be tailored to specific use cases, enhancing the overall effectiveness of AI systems.In this clip
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Practical AI
Threat modeling LLM apps
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