COGNITIVE WORLD and QAI.ai are partnering. Through a Field of Use license CogWorld will be powered by QAI for optimized engagement within its growing ecosystem of buyers and sellers of artificial intelligence solutions.
QAI is a patent-pending unbiased reinforcement learning platform for collective intelligence. This video hypothetically depicts one of an indefinite number of applications for QAI. Here, consider QAI optimizing engagement of content assets (all forms of media), nodes (company and individual profiles), and the formation of ecosystem niches (via dynamic self-organized clustering). Visit QAI.ai for more details on QAI.
QAI (Quantum Artificial Intelligence) to power COGNITIVE WORLD
Using the labeled images below, we describe how QAI is used and configured to power the intelligence of a social networking site based upon Drupal. In our example let us say that the Drupal site uses a Sql database to store content. Within Drupal nodes there are Sql language queries. These queries instruct the Drupal node to request content from the Sql server, which in turn extracts and provides the requested content from the Sql server database.
QAI Cognitive ReactorsTM may be viewed as Sql servers with the difference being the reactors contains dynamic knowledge, which is constantly in a state of learning and dynamic self-organization, i.e. it is not static. Continuing with our example, in order to harness QAI real-time machine learning and self-organizing quantum signaling, the Drupal node makes a Sql query to a QAI node labeled 5 in the below image. The QAI node then translates the Sql query into a QAI query and the node then injects the translated query into the reactor, labeled 4 (the sphere) in the images.
Once the QAI query injection has taken place quantum signaling and real-time machine learning engage and deep networks are formed to process the query. When reactor information entropy stabilizes (measured by quantum signaling neurons within the QAI reactor) the result is provided back to the QAI node that originally made the query. The reactor response is translated into the Sql language in the QAI node and sent back to the Drupal node, which initiated the QAI query. The Sql query now cached within the Drupal node is then used by Drupal to query the Sql server to obtained the content from the Sql server database, which QAI knowledge processing has instructed.
The QAI reactor maintains active self-organizing deep learning networks that reflect what content is available (or missing for that matter) within the associated Sql database(s). It also maintains relationships contained within the Drupal nodes and how this relates to the Sql content. This constantly evolves, with QAI acting as the brain for both Drupal and the Sql server. There are many ways to use the QAI Cognitive ReactorTM, this is just one (relevant) example.