Hofstadter's strength is his ability to stay focused on the highest level cognition problem. His theory is that analogies are the core of human cognition. His main work revolves around discovering how extensive human ability to think using analogies is.
I especially like his attempts to understand and capture the high level cognition in simple toy problems. His `copycat` and `Letter Spirit` programs illuminate the problem and his thinking in very clever way.
The current AI and ML research is building things bottom up and there is still significant gap before we reach the high level cognition that Hofstadter is interested in. What is the representation that binds low level and high level cognition and allows high level fluid concepts to be used as analogies from one domain to next with just one or two examples? Style transfer, variational autoencoders and transfer learning are very limited in this regard.
Challenges for deep learning:
* Deep Letter Spirit. Show 1-3 examples of lowercase letters of the roman alphabet in some font and have an algorithm that understands the style and completes the rest of the alphabet in the same style.
I especially like his attempts to understand and capture the high level cognition in simple toy problems. His `copycat` and `Letter Spirit` programs illuminate the problem and his thinking in very clever way.
The current AI and ML research is building things bottom up and there is still significant gap before we reach the high level cognition that Hofstadter is interested in. What is the representation that binds low level and high level cognition and allows high level fluid concepts to be used as analogies from one domain to next with just one or two examples? Style transfer, variational autoencoders and transfer learning are very limited in this regard.
Challenges for deep learning:
* Deep Letter Spirit. Show 1-3 examples of lowercase letters of the roman alphabet in some font and have an algorithm that understands the style and completes the rest of the alphabet in the same style.
* Bongard problems solver.