The Deep Nets are the hot thing these days in machine learning research. So hot that institutes are being established to study the social consequences of AI overtaking humanity and the White House has concerns regarding AI. Now every respecting sceptic should ask a question: is humanity really that close to solving the secret of intelligence? Or maybe this is just hype like in the 50'ies and 80'ies?
This is a long discussion. I will post many articles on that in the future hopefully. Here lets dissect a few popular myths:
- Convolutional deep nets solve perception. It is true that these systems have won ImageNet by a substantial margin and often can classify the content of the image accurately. It is also known that they get fooled by stuff that certainly would not fool a human. So that indicates that there is something missing. I think that we have somewhat shallow understanding of what perception really is. Vision is not about just categorising what we see. In fact we more often than not ignore the class of what we see. Humans or animals are more interested with affordances, namely "can I perform an action on what I