[sgt101]

The final 20 or so slides about building general AI using deep learning strike me as really interesting. Seymour Papet said that if you can fit concepts into your cognitive architecture then they are learned. I think that this part of the presentation speaks to a need to demonstrate this as "learning" proper. It's strange, because I believe that this needs to happen, but the idea that you would do it with an "all nn all the way down" architecture, rather than breaking out into a symbolic layer a-la SOAR just seems odd.