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 ...

Synthetic data— artificial data that closely mimic the properties and relationships of real data—is not a new idea but recent technological advances have brought it to prominence as a potentially ...

Advancements in Natural Language Processing (NLP) models and generative artificial intelligence (GAI) models have fundamentally changed the way that we think of human interaction—think AI chatbots and ...

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 ...

As artificial intelligence models continue to evolve at ever-increasing speed, the demand for training data and the ability to test capabilities grows alongside them. But in a world with equally ...

Synthetic data has been one of the biggest new trends of the past two years. Our contributors look ahead to the development ...

Synthetic data generation has emerged as a crucial technique for addressing various challenges, including data privacy, scarcity and bias. By creating artificial data that mimics real-world datasets, ...

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 ...

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 ...