In accordance with the translation , machine learning is used to train it to teach himself computer by filtering the data . Machine learning algorithms in very handy this could require thousands of CPU -based server for analyzing the amount of data that is very, very large .
However , this is a job that is very suitable for Tesla GPU -based accelerators . Tesla is an extra strong version of the chip that is used to beat up the ranks of gamers aliens and is now widely used to solve a variety of visual computing problems quickly and efficiently .
If you work with images and videos , you would use Adobe software every day . Adobe Creative Cloud is now activating more than 1.8 million users to access the device including applications that use GPU acceleration as Premiere Pro , After Effects , and Photoshop all over the world .
Now the R & D team is pushing the Adobe Creative Cloud that can do much more , using CUDA GPUs to help them build an image processing device that can study in depth (deep learning image processing tool) .
Deep learning or learning in depth could be an obstacle . However , Adobe's software in the future can use this technology to drive a variety of new creative possibilities .
For example , the application can automatically recognize a font style of many images to help users choose the right font for their creative projects . It can even help identify the sentiment of the picture and the elements in a work to help users quickly find another image that presents a sense of identical or similar aesthetics .
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" The move to the Creative Cloud we have encouraged an era of innovation in all directions Adobe . Machine learning with GPU acceleration open the door to a variety of exciting features and capabilities that can speed up the creative process and make your work look different from the others . " said David Howe , director of the Digital Imaging Engineering at Adobe in a press release received merdeka.com ( 7/4 ) .
source:http://www.merdeka.com/
