I had a couple of things running through my mind -- 1) "Deep learning algorithms are very good at one thing today: learning input and mapping it to an output. X to Y. Learning concepts is going to be hard." Andrew Ng.
I guess I take that to be an acid test of where the big guys are with concepts. 2) "brain inspired", "physics inspired", "math inspired," X-inspired, etc-inspired, hybird-inspired... It seems all AGI approaches take the "inspired by" approach. The only approach that is not deliberately inspired by some discipline, but aspires to the actual thing: Colin Hayes' approach. There is nothing wrong with the "inspired by" approach, of course. Mike ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
