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Karpathy mentions offhand in this video that he thinks he has the correct approach to AGI but doesnt say what it is. Before that he lists a few common approaches, so I assume it's not one of those. What do you think he suggests?
P.S. If this worries you that AGI is closer than you expected do not watch Jeff dean's overview lecture of DL research at Google.
The overview lecture doesn't really get me worried. It basically means that we are at the point where we can use machine learning to solve well-defined problems with plenty of training data. At the moment that seems to require a human machine learning expert and recent Google experiments suggest that they are confident to develop an API that can do this without machine learning experts being involved.
At a recent LW discussion someone told me that this kind of research doesn't even count as an attempt to develop AGI.