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
Adaptability is one of the key cognitive abilities that defined us as humans. Even as babies, we can intuitively shift between similar tasks even if we don’t have prior training on them. This contrasts with the traditional train-and-test approach of most artificial intelligence(AI) systems which require an agent to go through massive amounts of training before it can master a specific task.
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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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Americans are less trusting of self-driving cars following two deadly accidents involving autonomous or semi-autonomous vehicles, with half of U.S. adults considering those automobiles less safe than human drivers, according to a new poll. A Morning Consult survey conducted March 29-April 1 among a national sample of 2,202 adults found that 27 percent of respondents said self-driving cars are safer than human drivers, while 50 percent said autonomous vehicles are less safe. Eight percent said the automobiles are on par with human drivers when it comes to safety.
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