Translations:FACTS About Building Retrieval Augmented Generation-based Chatbots/60/zh: Difference between revisions

    From Marovi AI
    (Importing a new version from external source)
     
    (No difference)

    Latest revision as of 08:52, 19 February 2025

    Information about message (contribute)
    This message has no documentation. If you know where or how this message is used, you can help other translators by adding documentation to this message.
    Message definition (FACTS About Building Retrieval Augmented Generation-based Chatbots)
    Building trust is paramount when deploying generative AI chatbots. To mitigate risks, guardrails for hallucinations, toxicity, fairness, transparency, and security are critical. Strong foundational models are increasingly getting better at these guardrails. However, there are still many possibilities of jail breaks, adversarial attacks, and other security issues. Apart from these security risks, generative AI-based chatbots are susceptible to derivative risks (explained below). Since our bots are all internal enterprise chatbots, our focus has been more on the enterprise content security and guardrailing for sensitive data. Below we summarize our learnings and insights for securing RAG-based chatbots based on our experience. Addressing these challenges is imperative to maintaining the integrity and security of RAG-based chatbots within corporate environments.

    在部署生成式 AI 聊天机器人时,建立信任至关重要。为了降低风险,防止幻觉、毒性、公平性、透明性和安全性等问题的防护措施是关键。强大的基础模型在这些防护措施上越来越好。然而,仍然存在许多越狱、对抗性攻击和其他安全问题的可能性。除了这些安全风险之外,基于生成式 AI 的聊天机器人还容易受到衍生风险(如下所述)的影响。由于我们的机器人都是内部企业聊天机器人,我们更关注企业内容安全和敏感数据的防护。以下是我们基于经验总结的关于保护基于 RAG 的聊天机器人的学习和见解。解决这些挑战对于维护企业环境中基于 RAG 的聊天机器人的完整性和安全性至关重要。