AI Drones Help Inspect Industrial Equipment

Artificial Intelligence, Features, Robotics, Smart Cities, Architecture/Engineering/Construction, Energy/Oil & Gas, Image Recognition, Machine Learning & Artificial Intelligence, Manufacturing, Tesla

Nadeem Mohammad, posted Sep 13 2017

Avita Systems, a GE Venture, turned to NVIDIA DGX Systems to enable advanced robotic inspection and automated defect recognition services across the oil and gas, transportation, and energy industries.

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Gradient Boosting, Decision Trees and XGBoost with CUDA

Artificial Intelligence, Features, CUDA, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Sep 12 2017

Gradient boosting is a powerful machine learning algorithm used to achieve state-of-the-art accuracy on a variety of tasks such as regression, classification and ranking.

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Gradient Boosting, Decision Trees and XGBoost with CUDA

Features, CUDA, Gradient Boosting, Machine Learning, XGBoost

Nadeem Mohammad, posted Sep 11 2017

Gradient boosting is a powerful machine learning algorithm used to achieve state-of-the-art accuracy on a variety of tasks such as regression, classification and ranking.

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Detecting Concussions with a Smartphone and Deep Learning

Artificial Intelligence, Features, cuDNN, GeForce, Healthcare & Life Sciences, Higher Education/Academia, Image Recognition, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Sep 11 2017

Researchers from University of Washington developed a smartphone app that can detect concussions and other brain injuries — whether on the sidelines of a sports game or at an accident site.

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NVIDIA Sponsors “Learning to Run” AI Competition at NIPS 2017

Artificial Intelligence, Features, Robotics, Healthcare & Life Sciences, Higher Education/Academia, Machine Learning & Artificial Intelligence, physics

Nadeem Mohammad, posted Sep 08 2017

Participants in the Neural Information Processing Systems (NIPS) conference “Learning to Run” competition are vying for the chance to win an NVIDIA DGX Station, the fastest personal supercomputer for researchers and data scientists.

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NVIDIA Researchers Release Trailblazing Deep Learning-Based Framework for Autonomous Drone Navigation

Artificial Intelligence, Features, Robotics, Autonomous, Image Recognition, Jetson, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Sep 07 2017

NVIDIA’s autonomous mobile robotics team today released a framework to enable developers to create autonomous drones that can navigate complex, unmapped places without GPS.

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AI Technology Automatically Records Soccer Matches

Artificial Intelligence, Features, Cloud, cuDNN, GeForce, Image Recognition, Machine Learning & Artificial Intelligence, Media & Entertainment

Nadeem Mohammad, posted Aug 31 2017

A Copenhagen startup developed a deep learning-based camera system that can detect where the action is on the soccer field, and automatically zoom and follow the ball – just like how a camera operator would do.

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Classifying Tattoos with Neural Networks

Features, Research, Cloud, cuDNN, DIGITS, Image Recognition, Machine Learning & Artificial Intelligence, Media & Entertainment, Tesla

Nadeem Mohammad, posted Aug 29 2017

With nearly 1.5 billion monthly visitors and 346,000 pictures of tattoos, Tattoodo is taking advantage of deep learning to help categorize the growing number of uploaded images.

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Microsoft Sets New Speech Recognition Record

Features, Research, Cloud, cuDNN, Higher Education/Academia, Machine Learning & Artificial Intelligence, Speech & Audio Processing, Tesla

Nadeem Mohammad, posted Aug 21 2017

Researchers at Microsoft announced they reached a 5.1% error rate which is a new milestone in reaching human parity for recognizing words in a conversation as well as professional human transcribers.

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Scaling Keras Model Training to Multiple GPUs

Features, Deep Learning, Keras, MxNet

Nadeem Mohammad, posted Aug 16 2017

Keras is a powerful deep learning meta-framework which sits on top of existing frameworks such as TensorFlow and Theano. Keras is highly productive for developers; it often requires 50% less code to define a model than native APIs of deep learning

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