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 ...

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 ...

Real data is not sufficient to train better artificial intelligence models, experts said at South by Southwest. But simulated data must be done right. Jon covers artificial intelligence. He previously ...

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 ...

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 ...

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 ...

* 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 ...

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 ...

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 ...

We used Tonic Fabricate to generate a fully synthetic email corpus, then RL fine-tuned an open-source model against it. The ...