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A guide to the 10 most common data modeling mistakes Your email has been sent Data modeling is the process through which we represent information system objects or entities and the connections between ...

The explosive use of big data, predictive analytics and other modeling techniques to help understand and drive outcomes in all types of organizations has significantly increased over the past decade.

A survey of reasoning behaviour in medical large language models uncovers emerging trends, highlights open challenges, and introduces theoretical frameworks that enhance reasoning behaviour ...

Data is at the heart of today’s advanced AI systems, but it’s costing more and more — making it out of reach for all but the wealthiest tech companies. Last year, James Betker, a researcher at OpenAI, ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

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 ...

ABSTRACT Statistical meteorological impact models are intended to represent the impact of weather on socioeconomic activities, using a statistical approach. The calibration of such models is difficult ...

The world is changing rapidly, and if businesses want to keep up, there is no alternative but to change with it. Customer behavior, market conditions, and the technological landscape are in a constant ...