Review: Raspberry Pi – anidees AI-PI (Aluminium-Gehäuse) [GERMAN/DEUTSCH]

Heute möchte ich euch ein Gehäuse für den Raspberry Pi vorstellen. Das besondere an dem anidees AI-PI ist, dass es aus Plexiglas und Aluminium besteht. Dadurch sieht es deutlich edler als herkömmliche Plastikgehäuse aus.

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Facebook’s Caffe2 AI tools get to iPhone, Android, and also Raspberry Pi

Your smart phone may soon have the possibility to determine items in photographs free of gaining access to the cloud

New intelligence can be included with mobile phones similar to the iPhone, Android products, and low-power computers similar to Raspberry Pi with Facebook’s new open-source Caffe2 deep-learning framework.

Caffe2 can be used to program artificial intelligence features into tablets and smartphones, allowing them to understand pictures, video clip, text message, and speech and be more situationally aware.

It is critical to note that Caffe2 isn’t an AI program, but a tool enabling AI to be programmed into smart phones. It takes just some lines of code to write learning models, which could then be included into mobile apps.

The launch of Caffe2 is extremely important. This means users will be ready to get image identification, natural language processing, and computer vision straight on their cell phone. That work is generally offloaded to remote servers in the cloud, with smart phones then connecting to it.

Mobile devices are obtaining more artificial intelligence capabilities. More cellular phones 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 smart phones are due to get the Bixby voice assistant, which will make using the handsets far easier.

Caffe2 can work within the power constraints of mobile devices. It works with mobile hardware to facilitate AI applications and create neural networks.

Caffe2 uses the computing power of latest mobile hardware to quicken up deep-learning jobs. By way of example, in smart phones, Caffe2 will harness the computing power of Adreno GPUs and Hexagon DSPs on Qualcomm’s Snapdragon cellular SoC.


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