The past few decades have witnessed an upsurge in data, forming the
foundation for data-hungry, learning-based AI technology. Conversational
agents, often referred to as AI chatbots, rely heavily on such data to train
large language models (LLMs) and generate new content (knowledge) in response
to user prompts. With the advent of OpenAI's ChatGPT, LLM-based chatbots have
set new standards in the AI community. This paper presents a complete survey of
the evolution and deployment of LLM-based chatbots in various sectors. We first
summarize the development of foundational chatbots, followed by the evolution
of LLMs, and then provide an overview of LLM-based chatbots currently in use
and those in the development phase. Recognizing AI chatbots as tools for
generating new knowledge, we explore their diverse applications across various
industries. We then discuss the open challenges, considering how the data used
to train the LLMs and the misuse of the generated knowledge can cause several
issues. Finally, we explore the future outlook to augment their efficiency and
reliability in numerous applications. By addressing key milestones and the
present-day context of LLM-based chatbots, our survey invites readers to delve
deeper into this realm, reflecting on how their next generation will reshape
conversational AI.

本文全面调查了基于大型语言模型（LLMs）的聊天机器人在各个领域的进化和部署，总结了基础聊天机器人发展、LLMs 演进，并提供了当前正在使用和开发中的基于 LLMs 的聊天机器人概述。我们将 AI 聊天机器人视为生成新知识的工具，探讨了它们在各个行业中的多样应用。然后，我们讨论了一些挑战，包括训练 LLMs 使用的数据和生成知识的滥用可能引发的问题。最后，我们展望未来，探索如何提升它们在众多应用中的效率和可靠性。通过介绍 LLMs-based 聊天机器人的关键里程碑和当今背景，我们的调查邀请读者深入研究这一领域，并思考它们的下一代将如何重塑对话型人工智能。