Tackling Ebola With GPUs

Features, Research, Cluster / Supercomputing, CUDA, Higher Education / Academia, Medical and Life Sciences, Tesla

Nadeem Mohammad, posted Oct 07 2016

A team of researchers from University of Illinois at Urbana-Champaign and Stanford University are using the Blue Waters supercomputer at the National Center for Supercomputing Applications (NCSA) to predict what antibody would most likely pair best with a protein that coats a virus. The work focuses on two strains of the Ebola virus, and multiple

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Imperial College Leveraging Deep Learning in Cybathlon’s Brain-Computer Interface Race

Events, Research, CUDA, cuDNN, GeForce, Higher Education / Academia, Machine Learning & Artificial Intelligence, Medical and Life Sciences

Nadeem Mohammad, posted Oct 06 2016

58 teams from 29 countries are participating in the world’s first ever “bionic Olympics” in Zurich, Switzerland where athletes with physical disabilities will compete side-by-side in six demanding disciplines, using the latest technologies. Researchers from Imperial College in London teamed up with volunteer athletes to compete in four events — Brain-Computer Interface (BCI) race, Powered

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Getting Vulkan Ready For VR

Vulkan, GameWorks, DesignWorks, VRWorks, GameWorks Expert Developer

James Jones, posted Oct 05 2016

Introduction

Authors: James Jones, Mathias Schott

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Lose It!’s New Food Recognition App Counts Calories

News, Research, cuDNN, DIGITS, GeForce, Image Recognition, Machine Learning & Artificial Intelligence, Media & Entertainment, Medical and Life Sciences

Nadeem Mohammad, posted Oct 04 2016

The diet app LoseIt! released a new deep learning feature called Snap It that lets users take photos of their food and then it automatically logs the calorie count and nutritional information. Using the NVIDIA DIGITS deep learning training system on four TITAN X GPUs, the company trained their network on a vast database of

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