First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

As more companies invest in generative AI (gen AI) for bespoke use cases and products, proprietary data is becoming increasingly important to training large language models (LLMs). Unlike ChatGPT, ...

Adam Stone writes on technology trends from Annapolis, Md., with a focus on government IT, military and first-responder technologies. Artificial Intelligence has the potential to transform a range of ...

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 ...

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.

“By switching to AI-generated synthetic data, businesses can work smartly and safely with data, eliminating privacy risks and enabling the free flow of data within an organization and even to third ...

Global tech executives are racing to deploy autonomous agents over the next two years, but in doing so they face a balancing act: How do you leverage data in a way that maximizes trust and confidence ...

Data has long been at the heart of nearly every organization. But as organizations adopt increasingly sophisticated artificial intelligence (AI) tools, the challenges around accessing and using ...

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 ...

Jēnna Reese is CEO of Connect Centric, a D.C.-based firm that helps Fortune 500s and large nonprofits execute technology initiatives. In the race to modernize with AI, a new kind of risk is quietly ...

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 ...