Intel invest in computer vision
Intel more and more focus on computer vision technology, software and mainly related hardware. In past, Intel just bought itseez company which is mainly known for Opencv and other related computer vision activity. Now, intel acquire Mobileye, which is another step to go forward against competitors like Nvidia in future intelligent autonomous cars.
History of Mobileye
Since 1999 the Mobileye focus on vision-safety technology related to driving assistance like Advanced Driver Assistance System. ADAS. The approach is different and important for this acquisition. When google try to build cheaper LIDAR sensor for autonomous vehicles, company like Mobileye believe that Mono vision camera is everything you need to understand the scene. Cheaper than Lidar and cheaper than stereo. Mono vision as a primary source of the information that can handle, traffic-sign, pedestrians, vehicles is key factor of success of this company. This is little bit strange for me personally. Stereo camera make sense like human eyes and some animals need to handle their mono vision eye placement by strange movement of the head. Simply, I think that two cameras, eyes are better than the only one. It is not a mystery, that number of eyes in nature is most probably 2.
This is citation from Mobileye web site
Computer vision Hardware and Software
Mobileye focus also on specific HW for computer vision called EyeQ chip more complex than for exampleprocessor. This processor category is System on Chip (SOC), specialized for car sensing.. There is 8xCPU, 18xComputer Vision Processors, Security module, Wide band Sensor interface, IO controller and iSRAM wih Boot ROM memory.. All is certified for automotive whit passive cooling..
Check all the other specification on website..
Good luck to Mobileye under intel. Great that deeplearning is not a place only for strong cuda machines.. Deep learning is for distributive learning between many agents. The training parts.. Classification could be handled by low power specific processors like EyeQ or CEVA. Where smarter architectures, vectors, specific float registers or XNOR convolutional neural nets with only binary representation could beat down brutal cuda power.
BTW XNOR is great, technology.. Check article later this month.