Artificial intelligence (AI) and machine learning (ML) systems have advanced significantly in recent years. Despite a wide range of impressive results, current AI is not intelligent in the biological sense. These systems are limited to performing only those tasks for which they have been specifically programmed and trained, and are inherently subject to safety hazards when encountering situations outside them. The issue is further limiting to DoD applications, where situations can be unpredictable and the ability to react quickly and adapt to dynamic circumstances is of primary importance.
The Lifelong Learning Machines (L2M) program seeks to achieve paradigm-changing developments in AI architectures and ML techniques. The program seeks to develop systems that can learn continuously during execution and become increasingly expert while performing tasks, are subject to safety limits, and apply previous skills and knowledge to new situations - without forgetting previous learning.
L2M consists of two technical areas. The first concentrates on the development of complete systems and their components; the second brings together researchers with diverse expertise to explore biological mechanisms that underlie learning, which will be translated into a new generation of computational architectures, mechanisms, and algorithms. Discoveries in both technical areas are expected to generate new methodologies that will allow AI systems to learn and improve during tasks, apply previous skills and knowledge to new situations, incorporate innate system limits, and enhance safety in automated assignments.
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