Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI models. Unlike generative diffusion models, the team's Discrete Spatial ...

At each sampling time instant, one observes system output and action to form discrete-time rewards. The sampled input-output data are collected along the trajectory of the dynamical system in ...

Discrete Global Grid Systems (DGGS) have emerged as a robust framework for organising and analysing geospatial data across the entire Earth. By partitioning the globe into a hierarchy of optimally ...

Electronic health record (EHR) adoption was driven, in part, by a recognition of the power of data. Given the complexities of healthcare informatics, though, the full potential of health data has been ...

In political science, data with heterogeneous units are used in many studies, such as those involving legislative proposals in different policy areas, electoral choices by different types of voters, ...

Traditional data architectures are rigid and siloed, limiting agility, experimentation and the cross-domain insights required ...

When generative artificial intelligence (genAI) burst into prominence with the release of ChatGPT in 2022, technically savvy business users quickly began experimenting. At that time, existing tools ...

When doing my research for this column I often come across discussion about the size of a fund and how bigger is not necessarily better. Let us just stop and think about that. Some fund managers argue ...

Handling large amounts of data is a prerequisite of digital transformation, and key to this are the concepts of data lakes and data warehouses, as well as data hubs and data marts. In this article, we ...