Generative Language Models gained significant attention in late 2022 / early 2023, notably with the introduction of models refined to act consistently with users' expectations of interactions with AI (conversational models). Arguably the focal point of public attention has been such a refinement of the GPT3 model -- the ChatGPT and its subsequent integration with auxiliary capabilities, including search as part of Microsoft Bing. Despite extensive prior research invested in their development, their performance and applicability to a range of daily tasks remained unclear and niche. However, their wider utilization without a requirement for technical expertise, made in large part possible through conversational fine-tuning, revealed the extent of their true capabilities in a real-world environment. This has garnered both public excitement for their potential applications and concerns about their capabilities and potential malicious uses. This review aims to provide a brief overview of the history, state of the art, and implications of Generative Language Models in terms of their principles, abilities, limitations, and future prospects -- especially in the context of cyber-defense, with a focus on the Swiss operational environment.

翻译：生成式语言模型首次引起广泛关注是在2022年末/2023年初，特别是随着细化模型以与用户对与人工智能的交互的期望一致的方式进行操作（对话模型）。可以说，公众关注的焦点是GPT3模型的这种改进--ChatGPT及其后续与辅助功能的整合，包括作为Microsoft Bing的搜索之一。尽管以前的大部分研究已经投入了大量的发展工作，但它们在各种日常任务中的表现和适用性仍然不清楚和有限。然而，它们在不需要技术专业知识的情况下进行更广泛地使用，部分原因是通过对话微调的能力，揭示了在实际环境中它们真正的能力范围，这引起了公众对它们潜在应用的兴奋和对它们的能力和潜在恶意使用的关注。本回顾旨在简要介绍生成式语言模型的历史、现状和原理、能力、局限性以及未来前景--特别是在网络防御的情境下，着重关注瑞士的操作环境。