John Pavlopoulos: Machine Learning for Ancient Languages

Ancient languages preserve the cultures and histories of the past. However, their study is fraught with difficulties, and experts must tackle a range of challenging text-based tasks, from deciphering lost languages to restoring damaged inscriptions, to determining the authorship of works of literature. Technological aids have long supported the study of ancient texts, but in recent years advances in artificial intelligence and machine learning have enabled analyses on a scale and in a detail that are reshaping the field of humanities, similarly to how microscopes and telescopes have contributed to the realm of science. Based on a recent survey [https://direct.mit.edu/coli/article/49/3/703/116160/Machine-Learning-for-Ancient-Languages-A-Survey], this talk will focus on published research using machine learning for the study of ancient texts written in any language, script, and medium, spanning over three and a half millennia of civilizations around the ancient world. By analysing the relevant literature, lessons learnt and promising directions for future work in this interdisciplinary field are highlighted. 👉 More information about the lecture series "Machines that understand?": https://dm.cs.univie.ac.at/teaching/machines-that-understand/ 👉 Research Group Data Mining and Machine Learning at the University of Vienna: https://dm.cs.univie.ac.at/ 👉 Playlist Machines that understand? https://www.youtube.com/watch?v=p7OWeHuk7bk&list=PLJlwxvcFTl1GBlssnfcM67pwls2SKUCn7

Видео John Pavlopoulos: Machine Learning for Ancient Languages автора Programming Prodigy