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Hybrid AI system delivers robust and reliable solutions to complex problems
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OUR CORE R&D / These systems range from individual
autonomous robotic platforms to large-scale, multi-agent systems
for information management, command & control
These systems range from individual autonomous robotic platforms to large-scale, multi-agent systems for information management, command & control
Our machine learning research and development identifies patterns in data using a variety of approaches, including reinforcement learning, deep learning, anomaly detection, and cluster analysis. We use these patterns to better understand the world and to make better predictions and decisions.
Hybrid AI system delivers robust and reliable solutions to complex problems
A framework for building artificial intelligence systems
A predictive health and maintenance app for critical energy equipment
A socially intelligent AI coach for predicting and maximizing team performance
A system that helps AI systems navigate novel situations
A tool that strengthens trust in machine learning
An immersive AR/VR space training platform
Autonomous learning applied to robotic swarm tactics
A system to help soldiers maintain situational awareness
An infrastructure for increasing the resilience of US Navy Ships
A system to formalize course-of-action (COA) modeling
A tool to prioritize data collection
Surveillance system providing detection of attacks targeting army installations
A new machine learning approach with probabilistic modeling
Tools that make DRL agents understandable and trustable
Causal models to explain learning
A system to better understand potential threats in space
An interactive researcher’s workbench for ATR algorithms
Supervisory HMI enabling practical autonomous robot direction
A secure neural network that protects sensitive information
Probabilistic representation of intent commitments to ensure software survival
A probabilistic programming language to simplify machine learning
A weather and climate forecasting tool for mission planning
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