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 ...

The rapid expansion of digital infrastructure has heightened data security risks across sectors. Traditional assessment methods, often reliant on fragmented ...

Shift left has become a rallying cry for the chip design industry, but unless coherent data can flow between the groups being impacted, the value may not be as great as expected. Shift left is a term ...

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.

Work-related injuries are a complex and costly problem. Musculoskeletal Disorders (MSDs) are among the most widely spread occupational issues in industries and services, with increasing expenses of ...

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, ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...