Forward to the past

I was listening to Hinton’s interview (on CBC Radio: http://nvda.ly/OioP3). He mentioned multiple times of possible break through on natural language understanding by using deep learning technology. It is definitely true that human reasoning is such a difficult task to modeling as it is so complex to be abstracted easily. While I watch my little boy grows, I was amazed every time he shows a new ability, ability to do something, and ability to understand/perceive something. When training my own model (on image instead), I start to gain more understanding of the model. Structure determines the function. In most cases, the training is more like a process of “trial and error”. It’s a big black box with complex structures and connections. One of the biggest advantage of such learning network is its ability to automatically learn the representation, or say to abstract things. With abstraction in our logical system, we are able to organize things, dissect things, compose things, and possibly to create new things. Given what the network can already see/imaging (http://goo.gl/A1sL8N), it’s likely down the few years later, a network on human language could help us to translate the languages that went extinct thousands years by simply seeing over and over those scripts. This would be so wonderful cause so many ancient civilization will start shine again. Maybe I should call this “Forward to the Past”.