Digital humanities scholars have developed a computational system to mine maps from nearly 100,000 digitized books from the 19th and early 20th centuries, discovering that just 1.7% of novels include maps, mostly at the beginning or end.
The data inputs that enable modern search and recommendation systems were thought to be secure, but an algorithm developed by Cornell Tech researchers successfully teased out names, medical diagnoses and financial information from encoded datasets.
Students in tech fields now need to target specific organizations that match their interests, skills and values, and tailor their application materials to those specific organizations.
Joachims, professor of computer science and information science and director of the Cornell AI initiative, will coordinate AI across research, education and operations.
An interdisciplinary project involving faculty, staff and graduate students is sparking collaborations among those interested in computational, digital and data-driven approaches to the study of history, languages and culture.
A new approach, called WildCAT3D, is making it easier to visualize lifelike 3D environments from everyday photos already shared online, opening new possibilities in industries such as gaming, virtual tourism and cultural preservation.
As researchers are racing to find greener ways to power AI, a new study explores a promising solution: analog in-memory computing, utilizing analog chips.
A Cornell research team has introduced a new method that helps machines make connections between what’s on the ground and how it represented on a map – an advance that could improve robotics, navigation systems and 3D modeling.