Building AI products that enhance mission effectiveness
At Shield AI, the development of our products is rooted in the concept of resilient intelligence. Informed by this idea, Shield AI develops robots that are adaptable and capable of succeeding in the face of unanticipated challenges.
Shield AI’s CTO Nathan Michael and several of our technical leaders have dedicated their careers to furthering resilient intelligence and building robotic systems which grow ever more capable in the face of the unexpected and the challenging. They have developed and demonstrated, in controlled laboratory settings, the capabilities which are the focus of Shield AI’s products today, tomorrow and in the approachable future: autonomous robotic systems operating in a group, collaborating, swarming, and teaming to achieve their operators’ goals.
LEVERAGE AI Fundamentals TO DRIVE TECHNOLOGY FORWARD
Shield AI is dedicated to shaping the future of artificially intelligent systems. Through our research-based approach to building and fielding products, we have developed Hivemind, a scalable artificial intelligence framework to field and operationalize AI.
Hivemind enables individuals and teams of unmanned systems to learn from their experiences in both real world and simulated environments, so that they can become better, stronger and more adaptable over ever shorter time periods. Today, Hivemind enables robots to autonomously access and explore GPS-denied areas such as building interiors and caves to gather mission-critical, ground-level intelligence on demand.
Hivemind strives to achieve self-directed learning which will enable teams of unmanned systems to execute a wide variety of rigidly bounded missions with minimal human input. This learning enables our robots to amplify the ability of human-in-the-loop operators. This will provide our customers with transformational strategic capabilities.
DEVELOP SCALABLE SOLUTIONS
Shield AI’s Hivemind framework represents scalable resilient intelligence. While Hivemind is used to power single-robot systems today, it will scale to multi-robot teams in the approachable tomorrow. The application of Hivemind will enable teams of intelligent, coordinated, robots to operate in complex, real-world environments full of unexpected obstacles.
Refine, Verify & Validate
With Hivemind, robotic systems acquire knowledge through experience. Continued use enables the system to perpetually learn. This, in turn, yields products that become increasingly effective while they process, validate, and refine their behavior based upon what has been learned.
At Shield AI, our products gain experience through both synthetic testing and real-world applications. Extensive scalable simulations built specifically for testing, verification, and validation enable synthetic experience generation. Our products use real-world experience to cross-validate and refine knowledge gained in simulation. By perpetually refining our products, Shield AI creates robust systems ready to take on the challenges facing our customers.