ACCELERATING THE ARMY’S AI STRATEGY


THE TOP 16: XTECHSCALABLE AI 2 FINALISTS


The xTechScalable AI 2 finals event will be held at the Association of the United States Army 2024 Annual Meeting and Exposition in October, and the winners will be posted to the xTech website shortly thereafter.


Anaconda, Inc.: Rasterizing Large Datasets for Course of Action (CoA) Support: Allows large data sets to be rendered directly onto the screen by aggregating data points per pixel on the display device, providing complete context for decision makers choosing CoA in the field.


Cenith Innovations LLC: AI-Enabled, Automated CoA Generation and Threat Visualization for Intelligence Preparation of the Battlefield (IPB): Provides faster and more accurate IPB, empowering leaders to understand the terrain, routes and plans necessary for complex obstacle breaching.


ColdQuanta, dba Infleqtion: Consolidating Locations of Enemy Unit Symbols with AI in Real Time for Visual- ization: Creates a concise, common operating picture, capitalizing on the widespread availability of comput- ing resources to deliver physics-based map solutions to Soldiers.


Credo AI: The Credo AI Governance Platform to Enable Army Adoption of an AI Risk Management Framework: Purpose-built for AI governance, providing a command center for end-to-end Governance, Risk and Compli- ance for AI systems.


DynamoFL: Scalable AI Testing to Identify and Mitigate Generative AI Model Vulnerabilities: Assists in incorpo- rating secure, private and compliant AI into operations, including AI system evaluations, model enhancement, risk remediation and system guardrails development with real-time observability.


Latent AI: Battle-Management of Edge AI T&E: Supports automated testing and evaluation of data, training labels, model training, and AI runtime deploy- ment, enabling fast and robust fielding time of model updates.


Next Tier Concepts Inc.: Nights Watch: Protecting the Army’s AI while the Army Protects America: Serves as a test harness and monitoring system to assess AI models robustness to natural and adversarial phenom- ena prior to model deployment.


Phoenix Operations Group: Center-of-Mass (CoM) and CoA Validation Analytics: Provides Intelligence Prepa- ration of the Battlefield analytics for CoM calculations and CoA validation, using ML techniques implemented with open-source libraries and will integrate with exist- ing technology stacks.


Protopia AI: Privacy Enhancement and Data Protection for Gen AI and LLMs using Stained Glass Transform: Protects data and preserves privacy by allowing AI algorithms to operate accurately without exposing raw sensitive information, unlocking the data-secure devel- opment and deployment of AI systems to enhance security.


Pytho AI: Intelligent and Interactive Battlespace Visu- alizations Powered by Mixture of Experts AI System: Reduces cognitive burden as an interactive battlespace visualization and analytics platform, with disruptive intelligence models and an intuitive user interface.


R-DEX Systems, Inc.: Wayfarer: Real-time Data Drift and Out of Distribution (OOD) Detection Package: Streamlines the process of keeping ML models aligned with production data by focusing on OOD samples, minimizing the labeling workload for analysts and ensuring models remain accurate over time.


Senix Robotics LLC: Multi-Layered AI Approach for Scalable Battlefield Intelligence and Decision Making: Addresses data overload and inefficient manual processes, using advanced ML and generative AI to process sensor inputs, cluster data and provide stra- tegic analysis.


Striveworks: Valor: A Platform- and Model-Agnostic Eval- uation Store: Simplifies and standardizes T&E, making it easy to measure, explore and rank model perfor- mance, working with any dataset, model or metadata.


Trail of Bits: ModelInspector: Detecting AI/ML Model Weaknesses via Bill-of-Materials (AIBOM) Based Anal- ysis: Creates, maintains and assesses a system’s AIBOM for weaknesses, and creates AIBOMs for systems and then analyzes them to detect data drift, data leakage risks and susceptibility to adversarial threats.


72


Army AL&T Magazine


Fall 2024


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120