Study uses neural networks to define Dada

Cornell researchers explored whether an algorithm could be trained to sort digitized Dadaist journals from non-Dada modernist journals – a formidable task, given that many consider Dada inherently undefinable.

Digital ag is Cornell’s newest radical collaboration initiative

Digital agriculture at Cornell has just been seeded for robust additional growth by being added as a strategic discipline area to the provost's radical collaboration initiative.

‘Hamilton’ producer among spring Milstein speakers

The multidisciplinary Milstein Program in Technology & Humanity will bring prominent thinkers to campus this spring for thought-provoking public events and workshops.

Built to last 90 days, Mars rover Opportunity ends mission after 15 years

The Mars rover Opportunity, NASA’s robotic geologist fitted with an array of tools to search for evidence of water, ended its mission Feb. 13 – three weeks after its 15th anniversary and long past its 90-day warranty.

Halpern elected to National Academy of Engineering

Joseph Halpern, the Joseph C. Ford Professor of Engineering, has been elected a member of the National Academy of Engineering.

Active Learning Initiative funds nine projects

Innovative projects to enhance undergraduate teaching and learning in nine departments have received funding administered by Cornell’s Active Learning Initiative.

People admit they trust news stories that contradict their views – for a price

Researchers at Cornell Tech found that people are far more likely to say they believe news stories that align with their own political views no matter what outlet they’re from. But when offered a cash bonus for accuracy, participants were more likely to trust the news stories that countered their views.

Study: AI may mask racial disparities in credit, lending

A method intended to evaluate racial disparities in lending decisions can yield very different results depending on tiny changes in how it guesses applicants’ races, according to a new Cornell-led study.

AI adjusts for gaps in citizen science data

Citizen science databases can be inconsistent, but Cornell researchers have developed a deep learning model that effectively corrects for location biases, leading to more reliable predictions.