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Air Force Research Laboratory Signs Artificial Intelligence CRADA with CrowdAI

CrowdAI, the leading no-code computer vision platform, announced it signed a five-year Cooperative Research and Development Agreement (CRADA) with the Space Vehicles Directorate of the Air Force Research Laboratory (AFRL). The agreement gives AFRL access to CrowdAI’s cutting-edge deep-learning tools and experts, while enabling personnel from both organizations to experiment with the country’s hybrid space Intelligence, Surveillance, and Reconnaissance (ISR) architecture and computer vision.

In addition to deep learning research and development, the agreement also provides a continued pathway for CrowdAI to support major Department of Defense exercises. Robert Miller, who leads government solutions for the company, said, “Exercises, such as RIMPAC, provide the bedrock to our military’s readiness.” Rim of the Pacific, or RIMPAC, is the largest joint military exercise in the world, held bi-annually, and is happening this summer.

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CrowdAI CEO Devaki Raj said that the recently awarded CRADA and upcoming military exercises are “precisely the kinds of opportunities we’re built for.” CrowdAI’s “no-code” computer vision platform, she continued, “is mission- and sensor- agnostic. We can ingest and process any type of pixel coming down from LEO today and use our AI to provide commanders with information dominance over the battlespace.”

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AFRL Technical Program Manager Ms. Charlie Jacka, leading the CRADA, explained that the Hybrid Space Architecture brings together commercial, allied, tactical, and national imagery collection systems, and that the Department of Defense has been trying to build data exploitation pipelines leveraging AI. CrowdAI technology offers a COTS, end-to-end solution that can process those various pixels and generate uniform, structured outputs.

“We are excited to have this opportunity to experiment with this cutting-edge AI platform. In the conflict of the future, air and space superiority and access to any particular ISR asset are not assured. So, being able to quickly pivot from sensor-to-sensor and to have computer vision capabilities pivot alongside them is how the Hybrid Space Architecture succeeds,” she commented.

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