Google Trains Two Billion Parameter AI Vision Model

Researchers at Google Brain announced a deep-learning computer vision (CV) model containing two billion parameters. The model was trained on three billion images and achieved 90.45% top-1 accuracy on ImageNet, setting a new state-of-the-art record. The team described the model and experiments in a paper published on arXiv. The model, dubbed ViT-G/14, is based on Google's recent work on Vision Transformers (ViT). ViT-G/14 outperformed previous state-of-the-art solutions on several benchmarks, including ImageNet, ImageNet-v2, and VTAB-1k.