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 ...

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 train artificial intelligence (AI) models, researchers need good data and lots of it. However, most real-world data has already been used, leading scientists to generate synthetic data. While the ...

AI systems are increasingly being integrated into safety- and mission-critical applications ranging from automotive to health care and industrial IoT, stepping up the need for training data that is ...

California advances AI safety with SB 53, requiring transparency and risk reporting. Anthropic backs the bill, calling it a “trust but verify” approach. AI-driven automation is the theme of this ...

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 ...

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 ...

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How does deploying an aircraft carrier affect the future readiness of the fleet? A new data-modeling tool aims to predict it. (MC3Hannah Kantner/Navy) When it’s time to make a decision about sending a ...