Microsoft researchers say their newest deep learning system beats humans — and Google
Two stories for the price of one! Microsoft’s deep learning project beats human recognition on a data set and Microsoft is modest about it. 😉
From the post:
The Microsoft creation got a 4.94 percent error rate for the correct classification of images in the 2012 version of the widely recognized ImageNet data set , compared with a 5.1 percent error rate among humans, according to the paper. The challenge involved identifying objects in the images and then correctly selecting the most accurate categories for the images, out of 1,000 options. Categories included “hatchet,” “geyser,” and “microwave.”
…
[modesty]
“While our algorithm produces a superior result on this particular dataset, this does not indicate that machine vision outperforms human vision on object recognition in general,” they wrote. “On recognizing elementary object categories (i.e., common objects or concepts in daily lives) such as the Pascal VOC task, machines still have obvious errors in cases that are trivial for humans. Nevertheless, we believe that our results show the tremendous potential of machine algorithms to match human-level performance on visual recognition.”
You can grab the paper here.
Hoping that Microsoft sets a trend in reporting breakthroughs in big data and machine learning. Stating the achievement but also its limitations may lead to more accurate reporting of technical news. Not holding my breath but I am hopeful.
I first saw this in a tweet by GPUComputing.