PhysicsAI 2021 Year in Review
A sampling of PhysicsAI’s 2021 year in review: ✅We trained a deep neural network in less than one hour to drive a 26-ton US Army truck to perform convoy leader …
PhysicsAI awarded DARPA contract for Air Combat Evolution (ACE) Technical Area 1
U.S. military researchers are asking artificial intelligence (AI) experts at PhysicsAI in Pacifica, Calif., to develop AI algorithms to enable future experimental high-performance unmanned combat aircraft to formulate teams of …
PhysicsAI awarded Phase II SBIR contract for Deep Reinforcement Learning for Model Training with Simulated Imagery
In this project PhysicsAI is developing a framework for using deep reinforcement learning (DeepRL) to create optimal training data from simulated imagery in order to train machine learning models with …
PhysicsAI awarded Phase II SBIR contract for On-the-Move Spatiotemporal Processing for Full Motion EO/IR Sensors
In this project, PhysicsAI is developing a spatiotemporal video perception capability based on end-to-end deep neural networks (DNNs) for exploiting full-motion EO/IR sensors mounted on vehicles to provide a real-time …
PhysicsAI selected by DARPA to compete in AlphaDogfight Trials
PhysicsAI will participate in a virtual competition designed to demonstrate advanced artificial intelligence (AI) algorithms that can perform simulated within-visual-range air combat maneuvering, colloquially known as a dogfight. Participants will …
PhysicsAI awarded Phase I SBIR contract for Deep Reinforcement Learning for Model Training with Simulated Imagery
PhysicsAI will develop a framework for using deep reinforcement learning to create optimal training data from simulated imagery in order to train machine learning models with improved accuracy, increased robustness, …
PhysicsAI awarded Phase I SBIR contract for On-the-Move Spatio-Temporal Processing for Full Motion EO/IR Sensors
In this Phase I project PhysicsAI is developing a system that will allow real-time on-the-move integrated spatiotemporal processing of full-motion video data from EO/IR sensors for detection of in-road and …
PhysicsAI awarded Phase II SBIR contract for Robotic Following using Deep Learning
In this Phase II project, PhysicsAI will develop, integrate, and demonstrate a prototype system that can incrementally learn robotic following behaviors on a large vehicle, using deep learning algorithms and …
PhysicsAI awarded Phase I SBIR contract for Robotic Following using Deep Learning
The Phase I effort will develop a concept design for a system using lifelong deep learning and inexpensive COTS sensors to perform robotic following with large vehicles. SBIR Topic A16-120 …