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The podcast delves into the various security risks faced by large language models, particularly focusing on prompt injection attacks and adversarial examples. Prompt injection attacks aim to manipulate prompts to bypass the model's security mechanisms, while adversarial examples introduce noise to prompts to generate incorrect or unsafe outputs. The report emphasizes the importance of addressing these risks, highlighting how adversarial examples differ from direct model manipulation and showcasing Tencent's prompt security evaluation platform for ensuring compliance with regulations.