AFAMS - ITPA
Immersive Technology Planning Application (ITPA): Streamlining XR for US Air Force Training
AI-Supported Decision Making in Hardware
The ITPA leverages AI-powered insights to assist users in selecting appropriate hardware solutions, thereby enhancing decision-making capabilities.
Overview
The Immersive Technology Planning Application (ITPA) is an AI-powered solution designed to streamline the selection and integration of XR technologies for USAF training. It addresses the inefficiencies of manual selection processes by automating technology scanning, providing data-driven insights, and offering personalized recommendations tailored to specific training needs.
The ITPA leverages generative language requests and PDF consumption to generate minimum requirements in JSON format, which are then used to filter results of x-API calls for devices. The application is cloud-based and prioritizes data security, with the potential for integration with Fed cloud systems and air-gapped AI models. It also assists users in selecting appropriate hardware solutions.
The impact of ITPA includes the democratization of XR technology selection, enhanced training outcomes, and accelerated adoption of XR technologies into training programs. Future expansion plans include real-time inventory integration through partnerships with retailers like Best Buy and Walmart, providing up-to-date availability and pricing data for comprehensive recommendations.
AI Driven Tech Selection
ITPA leverages AI-powered analysis to provide personalized recommendations for immersive technologies, streamlining the technology selection process.
Multi-Sector Capability
The ITPA's potential for integration with 3rd party systems and air-gapped AI models highlights its multi-sector capability for healthcare, enterprise & other sectors outside of national defense.
ITPA Technical Specifications
1. Purpose
To streamline the integration of XR technologies (VR/AR) into USAF training programs.
To automate technology discovery, evaluation, and selection based on specific training needs.
2. Functionality
Data Acquisition Module:
Crawls websites, databases, and other sources for information on immersive technologies.
Extracts data on specifications, reviews, and security assessments.
AI-Powered Analysis Module:
Employs a custom-tuned Gemini 1.5 Large Language Model (LLM).
Analyzes technical data, user feedback, and security assessments.
Identifies key features, capabilities, and potential risks.
Evaluates technology suitability for specific training scenarios.
User Interface (UI) and Decision Support:
Allows users to input training requirements and constraints.
Generates personalized recommendations for suitable technologies.
Presents recommendations in a clear and concise format.
Feedback and Continuous Improvement:
Incorporates user feedback to refine recommendations.
Improves accuracy and relevance over time.
3. AI Technology
Custom-tuned Gemini 1.5 LLM.
Selected for data processing, technical language understanding, and logical reasoning.
4. Implementation Requirements
Software:
Gemini 1.5 API
Python libraries for data processing and analysis
Web framework for UI development
Hardware:
Servers and processing units capable of handling LLM computational demands
Data:
Comprehensive datasets of immersive technologies, training scenarios, and user feedback
5. Testing and Validation
Metrics: Accuracy of technology identification, relevance of recommendations, and data processing efficiency.
6. Security and Privacy
Encryption, access controls, and regular audits to protect sensitive data.
7. Data Sources
VR/AR comparison websites, manufacturer websites, and public databases.
8. Future Development
Phased rollout with pilot deployment.
Potential for automated training content generation and predictive modeling.
