Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

This article is part of our coverage of the latest in AI research. What is the next step toward bridging the gap between natural and artificial intelligence? Scientists and researchers are divided on ...

Deep learning shows a lot of promise in healthcare, especially in medical imaging, where it can help improve the speed and accuracy of diagnosing patient conditions. But it also faces a serious ...

Researchers have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data. The team introduced a self-supervised ...

AI has classically come in three forms, supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is where AI is given many example scenarios and the right answer for ...

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful. For a decade now, many of the most impressive ...