Horovod is a distributed training framework for TensorFlow, Keras, and PyTorch. The goal of Horovod is to make distributed Deep Learning fast and easy to use.
Source: github.com
Position Map Regression Networks (PRN) is a method to jointly regress dense alignment and 3D face shape in an end-to-end manner. In this article, I’ll provide a short explanation and discuss its applications in computer vision. In the last few decades, a lot of important research groups in computer vision have made amazing advances in 3D face reconstruction and face alignment.
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Deep learning has been at the forefront of the so called AI revolution for quite a few years now, and many people had believed that it is the silver bullet that will take us to the world of wonders of technological singularity (general AI). Many bets were made in 2014, 2015 and 2016 when still new boundaries were pushed, such as the Alpha Go etc. Companies such as Tesla were announcing through the mouths of their CEO’s that fully self driving car was very close, to the point that Tesla even started selling that option to customers [to be enabled by future software update].
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The Intel AI Lab has open-sourced a library for natural language processing to help researchers and developers give conversational agents like chatbots and virtual assistants the smarts necessary to function, such as name entity recognition, intent extraction, and semantic parsing to identify the action a person wants to take from their words. The first-ever conference by Intel for AI developers is being held Wednesday and Thursday, May 23 and 24, at the Palace of Fine Arts in San Francisco. The Intel AI Lab now employs about 40 data scientists and researchers and works with divisions of the company developing products like the nGraph framework and hardware like Nervana Neural Network chips, Liu said.
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