As artificial intelligence (AI) moves beyond experimentation to industrial-scale deployment, questions around privacy, ethics, and accountability continue to be asked. With so much attention focused ...

The tangible world we were born into is steadily becoming more homogenized with the digital world we’ve created. Gone are the days when your most sensitive information, like your Social Security ...

Deepfakes have moved from novelty to material enterprise risk, reshaping how organizations assess privacy, security, brand integrity and ...

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 ...

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 ...

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

The first time synthetic data was used to mimic real-world data was in 1993 by Donald Rubin. He created data that was statistically like genuine data, but without the risk of privacy compromise. With ...

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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DUBLIN--(BUSINESS WIRE)--The "Synthetic Data Generation - Global Strategic Business Report" has been added to ResearchAndMarkets.com's offering. The global market for Synthetic Data Generation was ...

The generation of synthetic data in healthcare has emerged as a promising solution to surmount longstanding challenges inherent in the use of real patient data. By replicating the underlying ...