Researchers in the Classics Faculty of the University of Oxford in collaboration with the Department of Humanities of Ca' Foscari University of Venice, the Department of Informatics of the Athens University of Economics and Business, and Google's DeepMind have begun applying state-of-the-art machine learning research to transform the study of ancient Greek texts. Ithaca is the first deep neural network that can aid historians in not only restoring the missing text of damaged inscriptions, but also identifying their original location, and establishing the date they were written. In a new research paper, published today by the scientific journal, Nature, the researchers have already used Ithaca to redate a series of important Athenian decrees from the 5th century BCE. 'The huge quantity of evidence from the ancient world, whether texts or objects, keeps on growing, and is increasingly beyond the scope of individual historians to master, even as we work to make sense of it and to make it more accessible. The application of AI to this data, as Ithaca demonstrates, presents incredible opportunities – ancient history has an exciting future.'

Predicting RNA (ribonucleic acid) structures may help accelerate the discovery and development of new drugs to treat diseases and disorders. A new Stanford study published in Science uses artificial intelligence (AI) machine learning to predict RNA structures with state-of-the-art performance results. "Few RNA structures are known, however, and predicting them computationally has proven challenging," wrote the Stanford scientists. "We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures." In molecular biology, RNA (ribonucleic acid) is involved in many important cellular functions.

Peter Norvig is a director of research at Google. Previously he was head of Google's core search algorithms group and of NASA Ames's Computational Sciences Division, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has taught at the University of Southern California and the University of California, Berkeley, from which he received a PhD in 1986 and the distinguished alumni award in 2006. He is coauthor of Artificial Intelligence: A Modern Approach, the leading textbook in the field.