Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

Can living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

A machine learning approach shows promise in helping astronomers infer the internal structure of stellar nurseries from telescope observations ...

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

The terms get mixed up constantly. In boardrooms, in classrooms, in startup pitches, even in technical documentation.You’ll hear someone say “AI system” when they really mean a predictive model.

Researchers from several Parisian institutions have worked together to develop a non-destructive approach to study how ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.