> You can go on thinking the solution is to find some sanctified Holy Grail > small set of parameters. A God given kernel of cognition. But meanwhile what > is working is just constantly unpacking structure by combining observations, > billions of features of it. The number is the thing. More than we imagined. > And contradicting but resolved in context. Moving first to networks, then to > more and more parameters over networks. That is what is actually working. > Allowing the network to blow out and generate more and more billions of > parameters, which can resolve contradiction with context.
I agree with you that "constantly unpacking structure by combining observations, billions of features of it." is part of what's needed for real-world AGI ... though I also think that the search for concise abstract models is another part of what's needed... And I don't think GPT3 is doing this "constantly unpacking structure by combining observations, billions of features of it." in the right way for AGI ... honestly Rob your own ideas feel way closer to the mark... ben ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T21c073d3fe3faef0-M87f7ca3201d34ea6297195fb Delivery options: https://agi.topicbox.com/groups/agi/subscription
