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.
Cornell researchers, in partnership with the technology company NVIDIA, have developed a method for creating digital images of cloth that more accurately captures the texture, sheen and translucence of textiles.
A new study shows that using large language models like ChatGPT boosts paper production, especially for non-native English speakers, but the overall increase in AI-written papers is making it harder to separate the valuable contributions from the AI slop.
In new research that puts the latest models to test in a 3D environment, Cornell scholars found that AI fares well with untangling basic knots but can’t quite tie knots from simple loops nor convert one knot to another.
Researchers in Cornell’s Matter of Tech Lab have developed CeraPiper, a fabrication system that creates customized sizes and shapes of ceramic pipes that can be fitted together and filled with water for environmentally friendly evaporative cooling.
