Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Moreover, four QR-based deep learning models were included for comparison, i.e., the quantile convolutional neural network (QCNN) model, the quantile long short-term memory network (QLSTM) model ...

Machine learning algorithms have been used to predict cancer progression, identify early signs of Parkinson’s disease, and ...

Several significant research studies related to Preventing Phishing Attacks for Cyber Threat Mitigation have been reviewed ...

Researchers review AI-powered inverse lithography, showing how deep learning boosts chip patterning precision and efficiency while facing scaling challenges.

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Liquid neural networks can spur new innovations in AI and are particularly exciting in areas where traditional deep learning models struggle.