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latest Raspberry Pi Project and I hope you guys like it.
GeauxRobot Raspberry Pi B+ Stackable Case: http://goo.gl/F1LAc8
SanDisk 8GB microSD http://goo.gl/21Sro2
NETGEAR 5-Port Switch http://goo.gl/Ds5csd
Anker [3-Pack] Premium 3ft Micro USB http://goo.gl/w8DT6V
Amazon USB Hub http://goo.gl/hWYhoN
Belkin RJ45 CAT 5e 3ft Cable http://goo.gl/dEOOLc
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Raspberry Pi 2 Projects – Raspberry Pi Cluster
Facebook’s Caffe2 AI tools travel to iPhone, Android, as well as Raspberry Pi
Your phone may soon be able to determine items in graphics without the need for getting access to the cloud
New intelligence can be added onto mobiles similar to the iPhone, Android OS gadgets, and low-power computer systems including Raspberry Pi with Facebook’s new open-source Caffe2 deep-learning framework.
Caffe2 enables you to program artificial intelligence features into smartphones and tablets, enabling them to recognize photographs, movie, text, and speech and be more situationally aware.
It is critical to note that Caffe2 isn’t an Artificial intelligence program, but a tool allowing AI to be programmed into smartphones. It takes just a few lines of code to write learning models, which can then be bundled into apps.
The launch of Caffe2 is crucial. It signifies users will be able to get image identification, natural language processing, and computer vision directly on their mobile. That work is typically offloaded to remote servers in the cloud, with smartphones then connecting to it.
Mobile devices are having more and more artificial intelligence capabilities. More cellphones are being bundled with Amazon’s Alexa and Google Assistant, while Apple’s Siri has been a staple in the iPhone for years. Samsung’s Galaxy S8 smartphones are due to get the Bixby voice assistant, which should make operating the mobiles easier.
Caffe2 can function within the power constraints of mobile devices. It works with mobile hardware to increase the speed of AI apps and create neural networks.
Caffe2 takes advantage of the computing power of latest mobile hardware to quicken up deep-learning jobs. For example, in smartphones, Caffe2 will use the computing power of Adreno GPUs and Hexagon DSPs on Qualcomm’s Snapdragon mobile chipsets.