Automatic Text Summarization: the plasticity of language
Automatic text summarization (ATS) techniques offer powerful solutions for generating accurate and informative summaries from textual data content. In our digital age, where an estimated 403 million terabytes of data are generated daily, it is vital that we are able to distil large amounts of textual content into focused summaries, containing just the salient details. In this article I provide an updated survey of state-of-the-art ATS methods, with a particular focus on how large language models models address the complexities and nuances of automated text summarization.