Research and advances in key technologies such as machine learning, computational game theory and autonomy can turn today's AI into AI fusion — a system that can augment human activities and increase quality of life, safety, productivity and efficiency in meaningful, transformative ways.

AI fusion focuses on accelerating distributed AI — enabling AI to evolve from today’s highly structured and deterministic, centralized architecture to a more adaptive and pervasive distributed architecture that autonomously fuses AI capability with the enterprise, the edge and AI-infused systems embedded on-platform. AI algorithms would autonomously discover and ‘move to the data,’ processing it at the edge or on-platform in real-time, and fusing the output with AI algorithms in the enterprise or on other platforms at the edge.

The benefits apply to countless domains, including healthcare, finance, agriculture, transportation, manufacturing, energy, smart cities and the environment. For the Department of Defense and the intelligence community, this innovation will significantly enhance situational awareness and decision-making by fusing information from systems and sensors across multiple domains — from the enterprise to the edge of the battlefield — to maximize mission effectiveness, reduce risk and save lives.

Carnegie Mellon has signature strengths in every domain needed to achieve AI fusion: AI frameworks and algorithms, AI-infused systems and microelectronics, AI fabric and abstraction, and human-AI interaction.