In the race to continue building more sophisticated AI deep learning models, Facebook has a secret weapon, billions of images on Instagram .
In research that the company is presenting today at F8, Facebook details how it took what amounted to billions of public Instagram photos that had been annotated by users with hashtags and has used that data to train their own image recognition models. They relied on hundreds of GPUs running around the clock to parse through the data, but they were ultimately left with deep learning models that beat industry benchmarks, the best of which achieved 85.4 percent accuracy on ImageNet.
If you’ve ever put a few hashtags onto an Instagram photo, you’ll know doing so isn’t exactly a research-grade process. There is generally some sort of method to why users tag an image with a specific hashtag, the challenge for Facebook was sorting what was relevant across billions of images.
When you’re operating at this scale —…