As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

The IMF develops a machine-learning nowcasting framework to estimate quarterly non-oil GDP in GCC countries in real time, ...

Unprofitable companies are outperforming profitable companies by over 14% this year, a trend that is unlikely to hold up in ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a chatbot is more humanlike and aware than it actually is, like believing it's ...

Artificial Intelligence is growing fast, and professionals now need both data science knowledge and Generative AI skills. These programs teach solid technical basics along with fundamental GenAI tools ...

The research, published in Nature Communications, aims to improve drug safety and effectiveness by accounting for genetic ...

For years, the artificial intelligence industry has followed a simple, brutal rule: bigger is better. We trained models on ...

Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

Vijayawada: Two academic books titled ‘Introduction to Artificial Intelligence’ and ‘Deep Learning’, authored by Dr Udayasri ...

Atomic-scale imperfections in graphene transistors generate unique wireless fingerprints that cannot be copied or predicted, ...