>Also, this article reeked of AGI ideas. Deep learning isn't trying to solve AGI. Reasoning and abstraction and high level AGI concepts that I don't think apply to deep learning. I don't know the path to AGI but I don't think it'll be deep learning. I think it would have to be fundamentally different.
I think that this is actually what the article is arguing.
from the article:
>Models closer to general-purpose computer programs, built on top of far richer primitives than our current differentiable layers—this is how we will get to reasoning and abstraction, the fundamental weakness of current models.
This means not using current deep learning ideas, and instead finding ways to integrate other types of programs (conventional algorithms, other types of ML) alongside Deep Networks.
I think that this is actually what the article is arguing. from the article: >Models closer to general-purpose computer programs, built on top of far richer primitives than our current differentiable layers—this is how we will get to reasoning and abstraction, the fundamental weakness of current models.
This means not using current deep learning ideas, and instead finding ways to integrate other types of programs (conventional algorithms, other types of ML) alongside Deep Networks.