This video explores the output of GANs described in this paper.

Abstract:

We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis. The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and also better disentangles the latent factors of variation. To quantify interpolation quality and disentanglement, we propose two new, automated methods that are applicable to any generator architecture. Finally, we introduce a new, highly varied and high-quality dataset of human faces.

Danny Shapiro, Senior Director of Automotive at NVIDIA talks about the NVIDIA DRIVE™ PX, an AI supercomputer its created to accelerate production of automated and autonomous vehicles. “Given the types of jobs out in the marketplace today and the lack of talent..there’s a lot of opportunity for anyone just getting started who can take courses to understand the fundamentals of computing today.” – Danny Shapiro

Deep learning and AI are fundamentally changing the way data is used in computation. They enable computing capabilities that will transform almost every industry, scientific domain, and public usage of data and compute.

The recent success of deep learning algorithms can be seen as the culmination of decades of progress in three areas: research in DL algorithms, broad availability of big data infrastructure, and the massive growth of computation power produced by Moore’s law and the advent of parallel compute architectures.

Deep learning has been employed successfully in such diverse areas as healthcare, transportation, industrial IoT, finance, entertainment, and retail, in addition to high-performance computing.

Examples shown in this video illustrate how the approach works and how it complements high-performance data analytics and traditional business intelligence.