BBaidu, Inc. is upping the ante in its fight with Google for image-recognition supremacy with what it hails as a record-setting computer vision system capable of recognizing different variations of the same image better than any other current artificial intelligence.  The secret?  A dedicated supercomputer.

Baidu’s homegrown neural network runs on a specially assembled cluster of 36 Linux servers each packing two six-core Intel Xeon E5-2620 processors, which can individually support up to 12 threads at a peak clock speed of 2.5Ghz. But the main source of the supercomputer’s image scanning power are the four Nvidia Tesla K40m graphic processing units included in every node, which manage a combined maximum of 617 trillion floating-point operations per second.

That’s roughly 20 percent more than the amount of computational capacity the US National Oceanic and Atmospheric Administration (NOAA) had at its disposal until a recent upgrade, horsepower that the researchers at Baidu employed to increase the quality of the images fed to their model for training purposes. The reasoning behind the decision is surprisingly straightforward.  The overall goal behind their investment in deep learning is to provide more accurate results for a growing number of image-based searches.