A short demo of how our artificially intelligent video camera built on a Raspberry Pi, can not only recognise a human face, but also identify a specific person and communicate autonomously with our IoT connected devices.
Facebook’s Caffe2 AI tools travel to iPhone, Android, and also Raspberry Pi
Your mobile may soon be able to know things in pics devoid of getting access to the cloud
New intelligence can be included to mobile phones such as the iPhone, Android products, and low-power computer systems just like Raspberry Pi with Facebook’s new open-source Caffe2 deep-learning framework.
Caffe2 allows you to program artificial intelligence features into tablets and cell phones, allowing them to understand photos, video, textual content, and speech and be more situationally aware.
You ought to take note that Caffe2 is not 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 applications.
The launch of Caffe2 is really important. It indicates people will be able to get image recognition, natural language processing, and computer vision right on their mobile phone. That process is normally offloaded to remote servers in the cloud, with smartphones then connecting to it.
Mobile devices are having more and more artificial intelligence features. More cellphones are being incorporated 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 ought to make operating the mobile phones far easier.
Caffe2 can work within the power constraints of mobile devices. It works with mobile hardware to hasten AI apps and create neural networks.
Caffe2 takes advantage of the computing power of latest mobile hardware to increase the speed of deep-learning tasks. As an example, in smartphones, Caffe2 will harness the computing power of Adreno GPUs and Hexagon DSPs on Qualcomm’s Snapdragon cellular chips.