Artificial intelligence and machine learning have transformed how we process information, make decisions, and solve complex problems. Behind every ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

New research shows AI language models mirror how the human brain builds meaning over time while listening to natural speech.

AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models.

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...

An analysis of LinkedIn job postings reveals the highest-paying AI jobs in the U.S. The data shows how responsibility and real-world execution now drive compensation.

The AI pioneer on stepping down from Meta, the limits of large language models — and the launch of his new start-up ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Medical imaging has become an essential tool for identifying and treating neurological conditions. Traditional deep learning (DL) models have made tremendous advances in neuroimaging analysis; however ...

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...