Classification

Stable Diffusion may amplify biases in its training data in ways that promote deeply ingrained social stereotypes.

Contract workers who help train the algorithms behind Google Search won a pay raise. Employees of U.S. contractors who evaluate the quality of Google Search’s results, knowledge panels, and ads will earn $15 per hour, a raise of roughly $1.

Large datasets often contain overly similar examples that consume training cycles without contributing to learning. A new paper identifies similar training examples, even if they’re not labeled.

Who would disagree that, if all people are mortal and Socrates is a person, Socrates must be mortal? GPT-3, for one. Recent work shows that bigger language models are not necessarily better when it comes to logical reasoning.

Training a model to separate the objects in a picture typically requires labeled images for best results. Recent work upped the ante for training without labels.

A machine learning model identified areas likely to have been damaged by Hurricane Leo as it swept through the southern United States.

A U.S. court ruled against an implementation of AI-powered software designed to catch students who cheat on academic examinations.

ViTDet, a new system from Facebook, adds an object detector to a plain pretrained transformer.

From Numbers to Names matches individuals to faces in publicly available images related to the genocide of European Jews between 1941 and 1945.

Convolutional neural networks separate proteins into functional families without considering their shapes.

A machine learning method could help chemists formulate pesticides that target harmful insects but leave bees alone. Researchers at Oregon State University developed models that classify whether or not a chemical is fatally toxic to bees.

A new machine learning method attempts to account for biases that may be held by certain subsets of labelers.

Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.

AiSCOUT uses computer vision to grade amateur footballers and recommends those who score highest to representatives of professional teams.

A drive-through system from UVeye automatically inspects vehicles for dents, leaks, and low tire pressure.