IBM touts improved distributed training time for visual recognition models

Two months ago, Facebook's AI Research Lab (FAIR) published some impressive training times for massively distributed visual recognition models. Today IBM is firing back with some numbers of its own. IBM's research groups says it was able to train ResNet-50 for 1k classes in 50 minutes across 256 GPUs -- which is effectively just the polite way of saying "my model trains faster than your model." Facebook noted that with Caffe2 it was able to train a similar ResNet-50 model in one hour on 256 GPUs using an 8k mini-batch approach. This would be a natural moment to question why any of this matters in the first place.