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 ...

Reasoning Models for Text Mining in Oncology: A Comparison Between o1 Preview, GPT-4o, and GPT-5 at Different Reasoning Levels A data set of 1052 patients with human epidermal growth factor receptor 2 ...

* 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 ...

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 ...

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.

Medical device innovation is laborious because of the high bar for validating that the technology does no harm. Patient recruitment for statistically powered trials stretches timelines and drives ...

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 ...

UK supercomputing power will be used to test a new facial emotion recognition system that relies on synthetic image data.

The Qualtrics 2025 Marketing Leader Business Intelligence Study shows that 56% of executives are overwhelmed by fragmented data and disparate sources. 29% of respondents said poor data quality and ...

A new study finds that while companies invest heavily in advanced algorithms, the quality of data feeding those systems remains deeply inconsistent, creating risks that could limit AI performance, ...