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Generative Language Models gained significant attention in late 2022 / early2023, notably with the introduction of models refined to act consistently withusers' expectations of interactions with AI (conversational models). Arguablythe focal point of public attention has been such a refinement of the GPT3model -- the ChatGPT and its subsequent integration with auxiliarycapabilities, including search as part of Microsoft Bing. Despite extensiveprior research invested in their development, their performance andapplicability to a range of daily tasks remained unclear and niche. However,their wider utilization without a requirement for technical expertise, made inlarge part possible through conversational fine-tuning, revealed the extent oftheir true capabilities in a real-world environment. This has garnered bothpublic excitement for their potential applications and concerns about theircapabilities and potential malicious uses. This review aims to provide a briefoverview of the history, state of the art, and implications of GenerativeLanguage Models in terms of their principles, abilities, limitations, andfuture prospects -- especially in the context of cyber-defense, with a focus onthe Swiss operational environment.

Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense