ORBAI's Bidirectional Interconnected Complementary Hierarchical Neural Networks are a novel, patented AI architecture using two interleaved spiking neural networks that work together to train each other to perform tasks in a way similar to how the human sensory cortices do. As a result, they train by simply sensing and interacting with the real world, learning from experience, context, and practice, not requiring canned training data nor explicit training sessions.

Imagine speech interfaces that converse with you fluently, and get better just by talking to you, and pick up your vocabulary and sayings, artificial vision systems that learn to see and identify objects in the world as they encounter them, and robots, drones, cars, toys, consumer electronics and homes  that use all of this together to truly perceive the world around them, precisely plan and control their actions and movement, and learn as they explore and interact, and truly become artificially intelligent and much more useful.