«Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains. Since there exists an infinite set of joint distributions that can arrive the given marginal distributions, one could infer nothing about the joint distribution from the marginal distributions without additional assumptions».
Source : Unsupervised Image-to-Image Translation Networks | Research
«Everything the vehicle “sees” with its sensors, all of the images, mapping data, and audio material picked up by its cameras, needs to be processed by giant PCs in order for the vehicle to make split-second decisions. All this processing must be done with multiple levels of redundancy to ensure the highest level of safety. This is why so many self-driving operators prefer SUVs, minivans, and other large wheelbase vehicles: autonomous cars need enormous space in the trunk for their big “brains.”. But Nvidia claims to have shrunk down its GPU, making it an easier fit for production vehicles».
Source : Nvidia says its new supercomputer will enable the highest level of automated driving – The Verge
Nvidia announced that it was partnering with Chinese web giant Baidu to build a platform for semiautonomous cars. (Baidu has approval to test autonomous cars in California as well.) Nvidia also built test cars, and was training them in parking lots and private roads prior to receiving this new approval from the California DMV. And this summer, a self-driving race car competition called Roborace announced that it was using the Drive PX2 in its vehicles.California has been a hotbed for autonomous testing, but that status is becoming decreasingly unique.
Source : California gives Nvidia the go-ahead to test self-driving cars on public roads – The Verge
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