cdmagurus.com
04-18-2017, 05:50 PM
New-intelligence-can be added to mobile devices like the iPhone, Android devices, and low-power computers like Raspberry Pi with Facebook's new open-source Caffe2 deep-learning framework.
Caffe2 can be used to program artificial intelligence features into smartphones and tablets, allowing them to recognize images, video, text, and speech and be more situationally aware.
It's important to note that Caffe2 is not an AI 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 release of Caffe2 is significant. It means users will be able to get image recognition, natural language processing, and computer vision directly on their phone. That task is typically offloaded to remote servers in the cloud, with smartphones then connecting to it.
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More... (http://www.pcworld.com/article/3190759/artificial-intelligence/facebooks-caffe2-ai-tools-come-to-iphone-android-and-raspberry-pi.html#tk.rss_all)
Caffe2 can be used to program artificial intelligence features into smartphones and tablets, allowing them to recognize images, video, text, and speech and be more situationally aware.
It's important to note that Caffe2 is not an AI 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 release of Caffe2 is significant. It means users will be able to get image recognition, natural language processing, and computer vision directly on their phone. That task is typically offloaded to remote servers in the cloud, with smartphones then connecting to it.
To read this article in full or to leave a comment, please click here (http://cdmagurus.com/article/3190759/artificial-intelligence/facebooks-caffe2-ai-tools-come-to-iphone-android-and-raspberry-pi.html#jump)
More... (http://www.pcworld.com/article/3190759/artificial-intelligence/facebooks-caffe2-ai-tools-come-to-iphone-android-and-raspberry-pi.html#tk.rss_all)