Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

A University of Michigan AI model diagnoses more than 50 brain disorders from MRI scans in seconds, with up to 97.5 percent accuracy.

Breakthrough AI foundation model called BrainIAC is able to predict brain age, dementia, time-to-stroke, and brain cancer ...

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...

Researchers at Pohang University of Science and Technology (POSTECH) have developed an artificial intelligence approach that addresses a key bottleneck in analog semiconductor layout design, a process ...

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

BrainIAC is a foundation AI model for brain MRIs that spots dementia risk, tumors, and aging better than old tech by ...