I take it with a grain of salt when a book author makes a comment like “This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default ...

Synthetic data allows regulators to test the resilience of critical infrastructure defenders under extreme hypothetical scenarios.

Currently, deep learning is the most important technique for solving many complex machine vision problems. State-of-the-art deep learning models typically contain a very large number of parameters ...

Microsoft and Tsinghua University have developed a 7B-parameter AI coding model that outperforms 14B rivals using only ...

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

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 ...

The question is simply unavoidable: Will we ensure our AI models continue to learn from the world, or will we let them learn from their own reflection?

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

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...