Translations:FACTS About Building Retrieval Augmented Generation-based Chatbots/45/zh: Difference between revisions

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Understanding the cost economics of generative AI-based chatbots involves several critical factors. The high costs of major and commercial LLMs can be unsustainable, with expenses adding up significantly across multiple use cases. Additionally, unseen expenses often accumulate as teams test various LLMs to meet specific needs. Moreover, when using commercial LLM vendor APIs, securing sensitive enterprise data requires guardrails to detect and prevent sensitive data leakage, as well as gateways for audit and legally permitted learning. There are also cost versus latency trade-offs to consider, as large LLMs with long context lengths typically have slower response times, impacting overall efficiency.

了解生成式人工智能聊天机器人的成本经济学涉及多个关键因素。主要和商业大型语言模型（LLM）的高成本可能难以维持，因为在多个使用案例中费用会显著增加。此外，随着团队测试各种LLM以满足特定需求，未见的费用往往会累积。此外，在使用商业LLM供应商API时，保护敏感企业数据需要设置防护措施，以检测和防止敏感数据泄漏，并设置审计和法律允许的学习网关。还需要考虑成本与延迟的权衡，因为具有长上下文长度的大型LLM通常响应时间较慢，影响整体效率。