This paper introduces the Contextual Evaluation Model (CEM), a novel method for knowledge representation and manipulation. The CEM differs from existing models in that it integrates facts, patterns and sequences into a single contextual framework. V5, an implementation of the model is presented and demonstrated with multiple annotated examples. The paper includes simulations demonstrating how the model reacts to pleasure/pain stimuli. The 'thought' is defined within the model and examples are given converting thoughts to language, converting language to thoughts and how 'meaning' arises from thoughts. A pattern learning algorithm is described. The algorithm is applied to multiple problems ranging from recognizing a voice to the autonomous learning of a simplified natural language.

The next big stage in the evolution of the Internet, according to many experts and luminaries, will be the advent of the Semantic Web–that is, technologies that let computers process the meaning of Web pages instead of simply downloading or serving them up blindly. Microsoft's acquisition of the semantic search engine Powerset earlier this year shows faith in this vision. But thus far, little Semantic Web technology has been available to the general public. That's why many eyes will be on Twine, a Web organizer based on semantic technology that launches publicly today. Developed by Radar Networks, based in San Francisco, Twine is part bookmarking tool, part social network, and part recommendation engine, helping users collect, manage, and share online information related to any area of interest. For the novice, it can be tricky figuring out exactly where to start.

We present Tracery, an authoring tool for casual users to build grammars to generate interesting stories. While many modern story generation systems work to maintain narrative causality, generative systems like Racter show that non-causal and even nonsensical systems also have expressive power. Using design principles of direct manipulation and flow, Tracery is designed to allow users to author more stories with greater ease, and fully explore the affordances of grammar-based story generation. A small pilot test of users were able to quickly author engaging stories, and praised the system for its fun and usability.