Turn Your Selfie Into Realistic VR Avatar

News, Research, Cloud, CUDA, Games, Machine Learning & Artificial Intelligence, Media & Entertainment, Signal / Audio Processing, Virtual Reality

Nadeem Mohammad, posted Nov 28 2016

California-based startup ObEN uses artificial intelligence to create a personalized and realistic 3D virtual self with just one smartphone image, and transports your virtual self into any AR and VR environment. ObEN, who was also chosen as one of 33 companies to participate in HTC’s VIVE X accelerator program, raised nearly $8 million for their

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Developing an Autonomous Bot is a Walk in the Park

Events, Features, Automotive, DIGITS, Embedded, Higher Education / Academia, Image Recognition, Jetson, Machine Learning & Artificial Intelligence, Robotics

Nadeem Mohammad, posted Nov 22 2016

Each November for the last decade, Tsukuba City in Japan has run a 2,000-meter race unlike just about any other in the world. What’s unusual is not the terrain – spanning parks, city streets, even indoor shopping malls – or the speed, the pace is a leisurely stroll. It’s the participants: each is an autonomous

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Winning Team Sets Record at SC16 Student Cluster Competition

Events, Features, Cluster / Supercomputing, GeForce, Higher Education / Academia, Tesla

Nadeem Mohammad, posted Nov 21 2016

A team from the University of Science and Technology of China (USTC) used 16 NVIDIA GPUs to pull off an SC first, winning both the first place prize for highest overall score and the highest LINPACK run at the SC16 supercomputing show in Salt Lake City, Utah. Held every at the annual SC conference, teams

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Lip Reading AI More Accurate Than Humans

Features, Research, CUDA, GeForce, Higher Education / Academia, Image Recognition, Internet / Communications, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Nov 18 2016

Researchers from Google’s DeepMind and the University of Oxford developed a deep learning system that outperformed a professional lip reader. Using a TITAN X GPU, CUDA and the TensorFlow deep learning framework, the team trained their models on over 100,000 sentences from nearly 5,000 hours of BBC programs. By looking at each speaker’s lips, the

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