Share Your Science: Using Deep Learning to Automatically Detect Geophysical Features

Research, CUDA, cuDNN, Development Tools & Libraries, Higher Education / Academia, Machine Learning & Artificial Intelligence, Oil & Gas, Share Your Science, Tesla

Nadeem Mohammad, posted Aug 19 2016

Chiyuan Zhang, PhD student at MIT talks about his joint project with Shell using GPUs and deep learning to automatically detect subsurface faults from seismic traces for oil and gas exploration. Using a Tesla K80 GPU, CUDA, cuBLAS and the cuDNN-accelerated Mocha.jl deep learning framework, the researchers were able to speed-up up their experiments nearly

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Deep Learning and Satellite Data Helping Map Poverty

Research, cuDNN, GeForce, Higher Education / Academia, Image Recognition, Machine Learning & Artificial Intelligence, Tesla

Nadeem Mohammad, posted Aug 18 2016

Stanford scientists developed a solution combining high-resolution satellite imagery with deep learning to accurately predict poverty levels at the village level. Using TITAN X and Tesla K40 GPUs with the cuDNN-accelerated Caffe and Tensorflow deep learning frameworks to train their convolutional neural networks, the researchers used the “nightlight” satellite data to identify features in the

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GeForce GTX 10-Series Pascal Based Notebooks Announced

GameWorks, VR

David Coombes, posted Aug 16 2016

Need cutting edge gaming performance in a laptop? Our GeForce GTX 10 Series notebooks use the revolutionary PASCAL architecture and are rated as VR Ready. This means you get the performance needed to develop and run AAA content including applications for Virtual Reality.

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GPU-Accelerated Robot Wins Amazon Warehouse Challenge

Features, News, Research, CUDA, cuDNN, GeForce, Higher Education / Academia, Image Recognition, Machine Learning & Artificial Intelligence, Robotics

Nadeem Mohammad, posted Aug 16 2016

Teams worldwide competed in the Amazon Picking Challenge, held at RoboCup 2016 in Leipzig, Germany, to see who’s robot can autonomously recognize objects and pick, and stow, the desired targets from a range of unsorted items. Working in collaboration with Delft Robotics, the team from Delft University of Technology in the Netherlands won the competition

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