NVIDIA has been doing some amazing cutting-edge research. In this video,they show off some of their latest work on realistic photo reconstruction. Could this put some Photoshop pros out of work?
NVIDIA’s latest AI breakthrough will allow developers and artists to create new interactive 3D virtual worlds for automotive, gaming or virtual reality by training models on videos from the real world.
Learn more: https://nvda.ws/2KOTPMc
Coreteks explores the future of GPUs and their role in AI.
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
Earlier today, I wrote a blog post about Video-to-Video synthesis done by researchers at Nvidia. The Washington Post highlights how the Silicon Valley company founded in 1993, best known for graphics cards, has embedded itself in nearly every autonomous vehicle effort.
See why in this video and how their AI deep learning is changing autonomous vehicles.
If you thought the technology behind Deep Fakes was impressive, then you will be floored by this demonstration of “Video-to-Video Synthesis.”
Best of all: the code is available on GitHub
Two Minute Papers has a video on the paper “Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation”
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.
Baidu’s Bryan Catanzaro presents “Deep Learning on GPU Clusters” and why GPUs are perfect for unlocking the power of AI.