This is the official repository for The Quest for Generalizable Motion Generation: Data, Model, and Evaluation. The repo provides a unified framework for generalizable motion generation, including ...

Medical imaging has become an essential tool for identifying and treating neurological conditions. Traditional deep learning (DL) models have made tremendous advances in neuroimaging analysis; however ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Abstract: The increasing complexity and volume of data in the retail sector necessitate robust mechanisms for ensuring data quality and governance. This paper presents a MATLAB-based analytical ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Artificial intelligence systems ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Willis, a WTW business, has integrated Moody’s detailed global flood data into its proprietary risk management tools, building upon its partnership with the company. In the past, Willis has ...

A new crowd-trained way to develop LLMs over the internet could shake up the AI industry with a giant 100 billion-parameter model later this year. Flower AI and Vana, two startups pursuing ...

Claybrook is an experimental AI model developed by Google and the model’s focus is on web development with an emphasis frontend tasks such as UI/UX coding. Claybrook leverages advanced techniques, ...