Artificial Intelligence (AI) models are only as good as the data on which they are trained. Yet gathering enough high-quality ...

As autonomous AI matures, the challenge is no longer collecting data but proving systems can handle rare, high-risk scenarios ...

Researchers from Tsinghua University and Microsoft have innovatively trained an AI model using synthetic data and Nvidia ...

Synthetic data is becoming an increasingly attractive tool for companies looking to accelerate their AI development. By simulating realistic scenarios, it can protect privacy, speed up model training ...

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While everyone focuses on synthetic data’s privacy benefits — yes, Gartner forecasts it represented 60% of AI training data ...

As AI systems become more sophisticated, the challenges of training them effectively—and responsibly—continue to grow. The use of real-world data often comes with concerns and roadblocks—privacy risks ...

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In a time when health systems are struggling to gain meaningful insights from data – and simultaneously aware that safeguarding patient privacy is essential – synthetic data offers a lot of potential.

As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...

A Chinese research team has built an artificial intelligence system that never touched real-world data, yet still runs on ...