Build Better IVA Applications for Edge Devices with NVIDIA DeepStream SDK on Jetson

Artificial Intelligence, Robotics, Smart Cities, Image Recognition, Jetson, Machine Learning & Artificial Intelligence, Tesla

Nadeem Mohammad, posted Nov 01 2017

Register Now for Early Access Program NVIDIA’s DeepStream SDK on Jetson makes it easy for developers to create robust, complex intelligent video analytics (IVA) capabilities for edge devices.

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Win up to $10,000 in the NVIDIA Jetson Developer Challenge

Artificial Intelligence, Features, Robotics, Automotive, Jetson, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Oct 23 2017

Calling all great developers, engineers, scientists, startups, and students!

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Webinar: Build Your Next Deep Learning Application for NVIDIA Jetson in MATLAB

Artificial Intelligence, Robotics, CUDA, cuDNN, Image Recognition, Jetson, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Oct 02 2017

Learn how you can use MATLAB to build your computer vision and deep learning applications and deploy them on NVIDIA Jetson.

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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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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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Intelligent Trash Pick-Up Robots Coming to an Office Near You

Research, Autonomous, cuDNN, Jetson, Machine Learning & Artificial Intelligence, Quadro, Robotics, Tesla

Nadeem Mohammad, posted Aug 03 2017

By Mark Theis, Michael Chacko, Ishan Mitra, Shruthi Jaganathan While you’re probably used to throwing away your own trash (hopefully), there’s no reason to with modern artificial intelligence (AI).

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Coming Right Up! High Schoolers Build Indoor Delivery Robot with NVIDIA Jetson TX2

Research, Autonomous, DIGITS, Jetson, Machine Learning & Artificial Intelligence, Robotics, TensorRT

Nadeem Mohammad, posted Aug 02 2017

By Grace Lam, Mokshith Voodarla, Nicholas Liu How long does it take to program an office delivery robot? Apparently, less than seven weeks.

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Inferencing Images 100x Faster with GPUs and TensorRT

Research, Higher Education/Academia, Image Recognition, Machine Learning & Artificial Intelligence, Robotics, TensorRT, Tesla

Nadeem Mohammad, posted Jul 25 2017

At this week’s Computer Vision and Pattern Recognition conference, NVIDIA demonstrated how one Tesla V100 running NVIDIA TensorRT can perform a common inferencing task 100X faster than a system without GPUs.

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NVIDIA Releases Latest JetPack 3.1 SDK with TensorRT 2.1 for AI at the Edge

News, CUDA, cuDNN, Jetson, Machine Learning & Artificial Intelligence, Robotics

Nadeem Mohammad, posted Jul 24 2017

NVIDIA released JetPack 3.1, the production software release for the Jetson TX1/TX2 platforms for AI at the edge. JetPack 3.1 doubles the deep learning inference performance for low latency applications for batch size 1.

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