Preparing real-world data for AI training is a labor-intensive process, often involving large-scale collection, tagging and validation. This can be time- ...

The graph below speaks volumes. Synthetic data will completely overshadow real data in AI models by 2030, according to Gartner. As synthetic data becomes increasingly pervasive in the months and ...

AI’s growth is limited by poor-quality data, not model size. Human expertise in data curation, decentralized feedback and ...

In today's rapidly evolving landscape of artificial intelligence (AI), two key concepts have emerged at the forefront of innovation: synthetic data and generative AI. Although these terms are ...

To feed these data-hungry models, researchers and organizations have increasingly turned to synthetic data ... major implication is that AI development could completely stall, leaving AI systems ...

As the name implies, the term refers to data that is artificially generated and used to replace real data ... of these models in the past year. Also: Can synthetic data solve AI's privacy concerns?

Elon Musk claims human-generated data for AI models is running out. This shortage could force a reliance on synthetic data, which may lower AI accuracy and reliability. However, careful management and ...

On Wednesday, Nvidia NVDA completed the acquisition of Gretel, a synthetic data startup ... and can be combined with real-world data to train AI models more efficiently and affordably.

While artificial intelligence continues to transform health care, the tech has an Achilles heel: training AI systems ... synthetic data is a viable resource for developing artificial intelligence ...

Major tech firms developing generative AI models ... real-world videos to assess their ability to recognise actions in those clips. Surprisingly, the models trained on synthetic data outperformed ...