Data Science for Science

  Credit: Acropolis Museum/Socratis Mavrommatis Ancient civilizations have held fascination for historians and anthropologists ever since humans became curious about the past. Deciphering life in civilizations past meant that excavated tools, vessels, assorted items, inscriptions etc. had to be unearthed and examined. The most informative of these would be the inscriptions on scrolls, papyri, stone, metal, or pottery. A lot of these inscriptions are incomplete due to damage and large chunks of the inscribed text are often illegible. Determining where the texts originated from can be a challenge since they may have been moved multiple times. Dating these texts is another challenge as radiocarbon dating and similar methods can't be used since they can damage the priceless artifacts. Enter AI. Researchers from DeepMind collaborated with researchers from the University of Oxford to develop Pythia , an ancient-text restoration system based on Deep Learning. The database used w...

Archaeologists, most exemplified in popular culture by the character of Indiana Jones, are more often seen as people who do a lot of manual field work: exploring hitherto unknown areas of land to find objects or patterns that would give some clues to the ancient past. They are now catching up with the rest of the sciences in utilising the amazing technology of AI. Uncovering long-abandoned ancient settlements in Madagascar, detecting nearly indiscernible bumps of earthen mounds left behind by prehistoric North American cultures, mapping Bronze Age river systems in the Indus Valley, and many more such activities are seeing the involvement of AI. Such activities called Landscape Archaeology are examples of areas where AI is helping scientists hunt for new archaeological digs as well as understand ancient cultures at large scale and great pace. So what data is used by AI to help with Landscape Archaeology? The near-ubiquitous availability of satellite data and other kinds of aerial ima...