Google Research and Stanford researchers test out a 1 billion connection, 9 layer, 16,000 core deep learning neural network (see geoff hinton and andrew ng talks on youtube) to recognize 20,000 different objects in images (with low accuracy but huge improvement over previous approaches).
This was done no with no pre-labeled images (except for fine tuning)! A brain that learned from raw images. The same algorithm can be applied to any data type (financial data, text, audio, images/video) without any human involvement (except gatheting of unlabelled data and running the system). Pretty much the artificial intelligence holy grail!
This was done no with no pre-labeled images (except for fine tuning)! A brain that learned from raw images. The same algorithm can be applied to any data type (financial data, text, audio, images/video) without any human involvement (except gatheting of unlabelled data and running the system). Pretty much the artificial intelligence holy grail!