The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning ...

A new connection between human and machine learning has been discovered: While conceptual regions in human cognition for long ...

Recent advances on deep learning models come at the price of formidable training cost. The increasing model size is one of the root cause, but another less-emphasized fact is that data scale is ...

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property.

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

The move comes not long after X (formerly Twitter) updated its own terms to ban model training, following a growing trend. Reddit, OpenAI, and even The Browser Company have also laid down similar ...

Federated learning is a widely used method for collaborative machine learning without sharing local data. In this approach, participants train models using their local data, and the model updates are ...

Purdue Agriculture researchers are harnessing the power of artificial intelligence (AI) and machine learning (ML) to amplify ...

GPUs are widely used to accelerate the training of machine learning workloads. As modern machine learning models become increasingly larger, they require a longer time to train, leading to higher GPU ...