EMERGING TECHNOLOGY AND MODERNIZING THE ARMY
XTECH FINALISTS MAKE SCALABLE AI AN ARMY REALITY
The U.S. Army xTech Program launched two AI-specific prize competitions in fiscal year 2024, supported by the PM IS&A and its modernization initiative, Project Linchpin. Matt Willis, Ph.D., director of Army Prize Competitions and Army SBIR Program, and his team launched xTechScalable AI in December 2023 for small businesses to develop comprehensive, scalable models capable of defending against universal AI threat vectors. The compe- tition offered a total prize pool of $370,000 and up to $8 million in follow-on Army SBIR contract awards to small businesses across the U.S.
XTechScalable AI 2 launched just months later in March 2024, with three topic areas in support of Project Linchpin, including: scalable tools for automated AI risk management and algorithmic analysis; scalable tech- niques for robust testing and evaluation of AI operations pipelines; and scalable techniques for center of mass and course of action analytics for intelligence preparation of the battlefield. The second iteration offered up to $603,000 in cash prizes and opportunities to submit proposals for a Phase I or Phase II Army SBIR contract valued at up to $250,000 or $2 million, respectively.
Read on to meet the competitions’ 24 finalists and get a glimpse into xTech’s world of innovation. THE TOP 8: XTECHSCALABLE AI FINALISTS
The program announced the xTechScalable AI winners in July 2024. Head over to the competition page of the xTech website to see who made the final cut.
Ad hoc Research: Adaptive AI Testing and Transparency: Unveiling DarkStax, the Future of Digital Twin Simula- tions in Military AI: Enhances AI systems' resilience against cyber threats by simulating and testing AI behaviors in diverse scenarios, ensuring robustness and reliability.
BlueRiSC, Inc.: AI Defense in Depth Architecture: Addresses threats in AI-based systems with modules for both prevention and detection, resulting in a comprehensive solution.
dMetrics: Transparent, Customizable and Traceable Information Extraction from Large Textual Sources: Learning platform built for non-technical experts, removing the need for coding or technical personnel and empowering analysts to read at scale through their own lens.
Eduworks: Lorica: AI Agent Microservices for Federated Data Security: Protects sensitive data and ML pipelines using a cluster of scalable, task-specific AI micromodels that can be deployed to detect adversarial attacks.
Expression Networks, LLC: TRUST-Large Language Model Operations (LLMOps) for the Army: Provides a data-, model- and vendor-agnostic solution to the challenges of LLMOps securely unleashing data intelligence at speed and scale.
Infleqtion: Secured AI for Positioning at the Edge, Navigation and Timing: Defends AI/ML systems against adver- sarial AI attacks, specifically targeting positioning, navigation and timing vulnerabilities, by fusing diverse data sources to identify and react to attacks.
Latent AI: Composable Hybrid Ensembles for Rapid AI Adaptation: Empowers developers with easy-to-use reci- pes to rapidly adapt AI models that are optimized and secured to address unknown attacks and vulnerabilities.
Quartus Engineering: Quartus Data Audit Tool: Enhances the data labeling and dataset management process, utilizing ML Zero-Shot technology to confirm datasets are reliable and recommend adjustments for faulty labels.
https://asc.ar my.mil
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