Learn how this new standard connects AI to your data, enhances Web3 decision-making, and enables modular AI systems.

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...

Hyperscale data centers are now powering AI models with a revolutionary architecture—at a staggering energy cost.

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

Count data modelling comprises a suite of statistical techniques dedicated to analysing non-negative integer-valued observations. Such data often arise in a variety of contexts including epidemiology, ...

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