Artificial intelligence and machine learning are reshaping how investors build and maintain portfolios. These tools bring ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

An AI-driven computational toolkit, Gcoupler, integrates ligand design, statistical modeling, and graph neural networks to predict endogenous metabolites that allosterically modulate the GPCR–Gα ...

Scientists have long suspected that hormones quietly tune how the brain learns, but the idea of a single, hidden “switch” has usually been more metaphor than map. What is emerging from decades of ...

OpenAI has signed a deal to acquire Neptune.ai, a specialised platform that helps track, analyse, and debug AI model training ...

Repeatable training means training the AI over and over again in a way that you can do the exact same steps each time. This ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...