Cameron Jones, a postdoctoral student at UC San Diego and one of the co-authors of the new paper, explains that Turing ...

Generally speaking, a useful benchmark should be both sufficiently difficult and closely aligned with reality: the problems ...

Although various methods have been proposed in academia to reduce model hallucinations, there is currently no remedy that can ...

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.

A Nigerian and PhD student in Applied Mathematics at Mississippi State University, Deborah Okoli, has built an easy-to-understand machine learning system for online markets. In an interview with The ...

The Busy Beaver Challenge, a notoriously difficult question in theoretical computer science, is now producing answers so ...

For pregnant women, ultrasounds are an informative (and sometimes necessary) procedure. They typically produce ...

The ADB–Cornell study finds that machine learning poverty maps often misfire, overestimating welfare in poor, rural, ...

EPFL researchers have developed Systema, a new tool to evaluate how well AI models work when predicting the effects of genetic perturbations. Subscribe to our newsletter for the latest sci-tech news ...

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...