florianletsch
Joined 12 years ago
Joined 12 years ago
Hype? For sure. But the current advances in autonomous vehicles will have a very real impact on the working life of the common truck driver (3.5 million in US alone), I think we all agree on that.
A small amount of neurons might already solve some problem you're having. The XOR problem can be learned by 4 neurons connected to each other.
When you want raw images or similar as an input and have it be classified into 100 classes (e.g. look up CIFAR-10 or CIFAR-100), you will need an architecture with many more neurons.
After all, ANN are simply a tool. Depending on the task, that tool might need to more elaborate. And when you have all those different possible architectures, you want a common way of naming them. Labels such as Deep Learning are simply nomenclature of talking about certain groups of artificial neural networks.
> NOTE: This is a DRAFT of the Go 1.6 release notes, prepared for the Go 1.6 beta. Go 1.6 has NOT yet been released. By our regular schedule, it is expected some time in February 2016.
The Google Vision Kit will run models on a custom neural processing chip connected to the Raspberry Pi Zero. With the DIY setup from the blog bost, the neural network runs on a "large pc" (potentially with GPU). Depending on the hardware you have at your disposal, you can run more complex (and therefore more powerful) neural networks. At the same time, you'll need wifi set-up and streaming to work. Completely embedded devices are easier to just put in the wild.
In theory, you should be able to use the models from the Vision Kit if you follow their instructions and just put the on a Raspberry Pi directly, and get an additional Movidius compute stick: https://developer.movidius.com/