In this part of the series of ‘100 Seconds Dot’, I will try discussing IoT, “Internet of Things” as we head to Artificial Intelligence (AI) finally. Cloud based “Amazon Echo” is just the tip of the iceberg. The thing will build on this platform. Here’s the demo on my Raspberry Pi with the help of two github repositories.
The music ‘On My Way Home (Sting)’ by The 126ers and ‘Piano March’ by Audionautix are used under Creative Commons (CC) licenses.
This AV is wholly produced on my LG G2, Samsung Galaxy S4 and Pi 2 android cluster.
My Blog: http://raqueeb.wordpress.com
100 Seconds Dot, ep. 11
Produced by Raqueeb Hassan
Facebook’s Caffe2 AI tools travel to iPhone, Android, and also Raspberry Pi
Your mobile may soon be capable of recognise items in images free of accessing the cloud
New intelligence can be combined with cellular devices just like the apple iphone, Android gadgets, and low-power PCs similar to Raspberry Pi with Facebook’s new open-source Caffe2 deep-learning framework.
Caffe2 allows you to program artificial intelligence features into tablets and smart phones, permitting them to realize photos, movie, text, and speech and be more situationally aware.
You should note that Caffe2 isn’t an Artificial intelligence program, but a tool making it possible for AI to be programmed into smartphones. It does take just a couple of lines of code to write learning models, which could then be incorporated into apps.
The launch of Caffe2 is critical. It means users will be in the position to get image identification, natural language processing, and computer vision directly on their phone. That process is often offloaded to remote servers in the cloud, with smartphones then connecting to it.
Mobile gadgets are receiving more and more artificial intelligence abilities. More mobiles are being incorporated with Amazon’s Alexa and Google Assistant, while Apple’s Siri has been a staple in the iPhone for many years. Samsung’s Galaxy S8 smartphones are going to get the Bixby voice assistant, which will make using the mobiles far easier.
Caffe2 can function within the power constraints of mobile gadgets. It works with mobile hardware to hasten AI applications and create neural networks.
Caffe2 uses the computing power of latest mobile hardware to accelerate deep-learning tasks. As an illustration, in smartphones, Caffe2 will harness the computing power of Adreno GPUs and Hexagon DSPs on Qualcomm’s Snapdragon cellular SoC.