Machine Learning — Image Upscaling

Artificial Intelligence and Machine Learning have enabled us to create applications that are almost magical in their abilities. In our first AI benchmark, we use Topaz Gigapixel AI to upscale a series of low resolution photos to higher resolution, while improving fine details at the same time.

Machine Learning — Image Classification

Teaching an AI to accurately recognize the contents of an image has always been one of the holy grails of Machine Learning research. Nero AI Photo Tagger is a consumer-oriented application that implements a simple way to use these algorithms. We let the software classify 2500 photos with tags like "car," "dog," or "flower."

Machine Learning — Tensorflow

Building an AI to solve complex problems first requires it to be trained through a large training data set that is evaluated repeatedly to generate a neural network that can later be put to work (also called inference). Google's Python-based Tensorflow is one of the most popular machine-learning software packages that supports both CPUs and GPUs. Setting up Tensorflow for the GPU is a bit complicated, so lots of algorithm development and training on small data sets still happens on the CPU. Training performance on the CPU can also beat the GPU when problem sizes exceed typical GPU memory capacities.