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.

Every synthetic dataset generated today trains tomorrow's models while potentially poisoning the ecosystem those models ...

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 ...

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

A Chinese research team has built an artificial intelligence system that never touched real-world data, yet still runs on ...

Databricks Inc. today introduced an application programming interface that customers can use to generate synthetic data for their machine learning projects. The API is available in Mosaic AI Agent ...

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 ...

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...

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 ...

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 ...