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”
Over $100m in 12 months backs natural language for the semantic web
Radar Networks is accelerating down the path towards the world’s largest body of knowledge about what people care about using Twine to organize their bookmarks. Unlike social bookmarking sites, Twine uses natural language processing technology to read and categorize people’s bookmarks in a substantial ontology. Using this ontology, Twine not only organizes their bookmarks intelligently but also facilitates social networking and collaborative filtering that result in more relevant suggestions of others’ bookmarks than other social bookmarking sites can provide.
Twine should rapidly eclipse social bookmarking sites, like Digg and Redditt. This is no small feat!
The underlying capabilities of Twine present Radar Networks with many other opportunities, too. Twine could spider out from bookmarks and become a general competitor to Google, as Powerset hopes to become. Twine could become the semantic web’s Wikipedia, to which Metaweb’s Freebase aspires. Continue reading “Over $100m in 12 months backs natural language for the semantic web”