Threat modeling LLM apps (Practical AI #283)
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Validating Language Model Outputs
This chapter explores the critical need for validating outputs from large language models (LLMs) to ensure reliability and security. It emphasizes integrating traditional NLP methods for assessing toxicity and factual accuracy, while discussing the challenges posed by vulnerabilities like prompt injections. The conversation also highlights the role of efficient, smaller models in enhancing the validation process and securing LLM applications in enterprise settings.
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