The Agent-R1 framework provides a path to building more autonomous agents that can reason and use tools in unpredictable, ...

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to ...

Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

AI is not limited to diagnostics or imaging. It also plays a transformative role in biomedical research, computational modeling, genomics and drug development. The authors highlight how ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

A specially trained algorithm could aid the search for biological activity both on the early Earth and on other worlds.

Soon, researchers may be able to create movies of their favorite protein or virus better and faster than ever before. Researchers at the Department of Energy's SLAC National Accelerator Laboratory ...

In rock-paper-scissors, the ideal strategy is simple: You should play a random move each round, choosing all three ...

AI-based evaluation of medical imaging data usually requires a specially developed algorithm for each task. Scientists have now presented a new method for configuring self-learning algorithms for a ...

The predictive ability of cough sound algorithms shows promise in detecting acute respiratory diseases, study finds. A machine learning algorithm for detecting and classifying acute respiratory ...

This August, the Department of Housing and Urban Development put forth a proposed ruling that could potentially turn back the clock on the Fair Housing Act (FHA). This ruling states that landlords, ...