New York University

Machine learning algorithms often struggle with geometry. A language model learned to prove relatively difficult theorems. 

A novel twist on self-supervised learning aims to improve on earlier methods by helping vision models learn how parts of an image relate to the whole.

Researchers took a step toward achieving a longstanding goal: One model that performs a whole lot of very different tasks. Scott Reed, Konrad Żołna, Emilio Parisotto and a team at DeepMind announced Gato.

Pretrained language models like GPT-3 have shown notable proficiency in few-shot learning. Given a prompt that includes a few example questions and answers (the shots) plus an unanswered question (the task), such models can generate an accurate answer.

Pretraining methods generate basic representations for later fine-tuning, but they’re prone to certain issues that can throw them off-kilter. New work proposes a solution.

In some animated games, different characters can perform the same actions — say, walking, jumping, or casting spells. A new system learned from unlabeled data to transfer such motions from one character to another.

The pandemic has pushed hospitals to their limits. A new machine learning system could help doctors make sure the most severe cases get timely, appropriate care.

The U.S. government’s effort to take advantage of AI has not lived up to its promise, according to a new report. Implementations of machine learning systems by federal agencies are “uneven at best, and problematic and perhaps dangerous at worst".