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：生成式语言模型在2022年末至2023年初引起了广泛关注，尤其是随着经过精细调整的模型的出现，这些模型能够与用户对人工智能交互的期望保持一致（即对话式模型）。公众关注的焦点可以说在于GPT3模型的此类改进——ChatGPT及其随后与辅助功能的集成，包括作为微软必应的一部分的搜索功能。尽管在此之前已有大量的研究投入于其开发，但其在各类日常任务中的表现和适用性仍不明确且局限于小众领域。然而，通过对话式微调，这些模型在无需技术专业知识的情况下得到了更广泛的应用，这揭示了它们在真实环境中的真正能力。这既引发了公众对其潜在应用的兴奋，也引起了对其能力及恶意用途的担忧。本综述旨在简要概述生成式语言模型的历史、现状及其在原理、能力、局限性和未来前景方面的影响——特别是在网络防御背景下，重点关注瑞士的运行环境。