Natural Intelligence

Deep natural language understanding (NLU) is different than deep learning, as is deep reasoning.  Deep learning facilities deep NLP and will facilitate deeper reasoning, but it’s deep NLP for knowledge acquisition and question answering that seems most critical for general AI.  If that’s the case, we might call such general AI, “natural intelligence”.

Deep learning on its own delivers only the most shallow reasoning and embarrasses itself due to its lack of “common sense” (or any knowledge at all, for that matter!).  DARPA, the Allen Institute, and deep learning experts have come to their senses about the limits of deep learning with regard to general AI.

General artificial intelligence requires all of it: deep natural language understanding[1], deep learning, and deep reasoning.  The deep aspects are critical but no more so than knowledge (including “common sense”).[2] Continue reading “Natural Intelligence”

Real AI for Games

Dave Mark’s post on Why Not More Simulation in Game AI? and the comments it elicited are right on the money about the correlation between lifespan and intelligence of supposedly intelligent adversaries in first person shooter (FPS) games.  It is extremely refreshing to hear advanced gamers agreeing that more intelligent, longer-lived characters would keep a game more interesting and engaging than current FPS.  This is exactly consistent with my experience with one of my employers who delivers intelligent agents for the military.  The military calls them “computer generated forces” (CGFs).  The idea is that these things need to be smart and human enough to constitute a meaningful adversary for training purposes (i.e., “serious games”).  Our agents fly fixed wing and rotary wing aircraft or animate special operations forces (SOFs) on the ground.  (They even talk – with humans – over the radio.  I love that part.  It makes them seem so human.) Continue reading “Real AI for Games”