Despite recent improvements to machine learning (ML) algorithms and assurance technologies, high levels of autonomy still remain elusive.
The reasons for this are twofold. First, data-driven ML lacks transparency, interpretability, and robustness and has unsustainable computational and data needs. Second, traditional approaches to building intelligent applications and autonomous systems that rely on knowledge representations and symbolic reasoning can be assured but are not robust to the uncertainties encountered in the real world.
DARPA’s newest artificial intelligence (AI) program, Assured Neuro Symbolic Learning and Reasoning (ANSR), seeks to address these challenges in the form of new, hybrid (neuro-symbolic) AI algorithms that deeply integrate symbolic reasoning with data-driven learning to create robust, assured, and therefore trustworthy systems.