Methanol-to-olefins (MTO) is a crucial non-petroleum route to produce light olefins like ethene and propene, which are essential for manufacturing ...

This important study describes long-range serial dependence of performance on a visual texture discrimination training task that manipulated conditions to induce differing degrees of location transfer ...

People interact with artificial intelligence (AI)-powered chatbots, which can be trained to take on certain demographic attributes like age and race, for information, entertainment, technical help, ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Flexible curriculum model allows real-time response to evolving social challenges faced by children, teens, and adults ...

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...

Zak-OTFS Waveform Required to Address the Unique Challenges of Delay Spread and Doppler Impairments in Space to Make ...

In biomedical modeling, the integration of mechanistic and data-driven approaches is reshaping how we interpret and predict complex biological phenomena.

Demis Hassabis, co-founder and CEO of Google DeepMind, has identified three specific areas where even the most advanced AI systems still fall short of human cognition. His remarks, delivered as a ...