Fake Data Crucial for Neural Network Learning.

Researchers are increasingly turning to synthetic data to supplement or even replace natural data for training neural networks. Synthetic data is proving useful in addressing concerns about facial recognition, as many facial recognition systems are trained with huge libraries of images of real faces, which raises issues about privacy and bias. Microsoft has released a collection of 100,000 synthetic faces for training AI systems, generated from a set of 500 people who gave permission for their faces to be scanned. The computer can label every part of every face, which helps the neural net learn faster.