The CyberText Technologies Project, headed by Professor Elaine Treharne, is funded by Stanford University School of Engineering CyberInitiative. Our project team has been cataloguing the history of dominant text-based human communication devices in an effort to identify common traits. These determinable traits could theoretically be used predictively to assess which modern-day technologies are most likely to succeed and what paths imminent text technologies may take. The project is responsible for creating a series of standardized measuring tools and schemas for analysis of these objects, as well as case-study databases for dominant text technologies ranging from Cuneiform tablets to modern-day print. From our databases, machine learning assesses the patterns that will help in forecasting the future of text technologies.
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