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 ...

In 2025, organizations operate amid escalating geopolitical tensions, data sovereignty restrictions, and stricter artificial intelligence (AI) regulations like the EU’s Cyber Resilience Act. These ...

With the rise of generative AI, synthetic images and text have become common knowledge -- but are you familiar with synthetic data? As the name implies, the term refers to data that is artificially ...

Synthetic data are artificially generated by algorithms to mimic the statistical properties of actual data, without containing any information from real-world sources. While concrete numbers are hard ...

Data is the life-blood of physical AI. Collecting real-life data is expensive. Generative AI and diffusion to create ...

COMMISSIONED: As with any emerging technology, implementing generative AI large language models (LLMs) isn’t easy and it’s totally fair to look side-eyed at anyone who suggests otherwise. From issues ...

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.

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* The Matrix analogy: Are we training AI inside simulations? Whether you're a data scientist, CTO, or just curious about how AI models learn, this episode offers a deep dive into one of the most ...

Editor’s note: This article, distributed by The Associated Press, was originally published on The Conversation website. The Conversation is an independent and nonprofit source of news, analysis and ...