AI Development Environment Applied Research
Abstract
This effort investigates cloud-native architectures, orchestration technologies, and collaboration techniques to support current and future Artificial Intelligence (AI) model development and machine learning operations (MLOps) tasks across a globally distributed workforce. Research will increase the effectiveness and efficiency of development platforms, decrease model development costs, optimize shared resources, and reduce the time required to integrate new AI capabilities into software products. This effort will provide the AI enabled Army of the future with low cost, rapid analytic and AI/ML solutions at the edge and enable accelerated algorithm development for faster delivery to the field. Less expensive AI/ML development by leveraging shared resources. The cited research is consistent with Under Secretary of Defense for Research and Engineering priority focus areas and the Army Modernization Strategy. Research in this Project supports the Army Science and Technology Network Portfolio and the Chief Digital and Artificial Intelligence Office (CDAO).
Document Details
- Document Type
- Project
- Publication Date
- Oct 01, 2025
- Source ID
- DE8_0602180A_2_2040_PB_2025
Related Documents
- Root: Artificial Intelligence and Machine Learning Technologies
- Child Accomplishment: Artificial Intelligence Environment Applied Research