Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

According to TII’s technical report, the hybrid approach allows Falcon H1R 7B to maintain high throughput even as response ...

Abstract: In industrial processes, accurate, real-time soft sensor modeling of key product indices is essential for optimal process control and improved product quality. However, the nonstationary ...

Hi, thank you for the great scPred model implementation! I have a question regarding the input normalization step during model training and prediction. In the training script, standardization is done ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Abstract: Transliteration normalization is a crucial task for low-resource languages, particularly for Mongolian, where noisy text from social media presents significant challenges. The frequent use ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Artificial Intelligence (AI) is revolutionizing climate modeling by enhancing predictive accuracy, computational efficiency, and multi-source data integration, playing a crucial role in sustainable ...

SAN DIEGO--(BUSINESS WIRE)--SqlDBM today announced that it has been selected as winner of the “Database Modeling Solution of the Year” award in the 4 th annual Data Breakthrough Awards program ...