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

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

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 ...

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, ...

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 ...

Think of artificial intelligence (AI) as a forensic magnifying glass... here is how it works. In the simplest terms, ...

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 ...

In the rapidly advancing landscape of Industrial IoT (Internet of Things), cybersecurity has taken on unprecedented importance. The proliferation of connected devices in industrial sectors has ...

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, ...