This paper presents a discussion of the relevancy of older natural language processing approaches compared to modern large language models (LLMs), with experimental results for a specific application: the segmentation of video transcripts. An analysis was conducted, if powerful modern LLMs are necessary for tasks such as text segmentation or if traditional and more efficient models – here TextTiling – suffice. In the end, LLMs provide comparable performance to the other models, but the results produced by TextTiling are promising and suggest a discussion about a trade-off regarding efficiency, performance, energy-consumption and other factors.