Foundational Machine Intelligence
Abstract
The Foundational Machine Intelligence program supported research on the foundations of artificial intelligence and machine learning and reasoning. One focus was on techniques that can efficiently process and "understand" massive data streams. Deeply layered machine learning engines were created that use a single set of methods in multiple layers (at least three internally) to generate progressively more sophisticated representations of patterns, invariants, and correlations from data inputs. These will have far-reaching military implications with potential applications such as anomaly detection, object recognition, language understanding, information retrieval, pattern recognition, robotic task learning and automatic metadata extraction from video streams, sensor data, and multi-media objects. Foundational Machine Intelligence also examined the human aspects of computing, with interest in collaboration, interaction and information exchange; non-symbolic representation/reasoning paradigms based upon a universal "cortical" algorithm; and modeling of human language acquisition by associating words with the real-world entities perceived through multiple modes of sensory input.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2013
- Source ID
- dd8493521f320126bd00f516731c42c0