Modeling and Simulation RFI_Counter_AI_TRL_Final.pdf

SPECIAL NOTICE: Program Executive Office (PEO) Intelligence, Electronic Warfare and Sensors and PEO Simulation Training and Instrumentation Request for Information Modeling and

Simulation Capabilities to Support Army Initiatives.

1. SYNOPSIS

The United States (U.S.) Army, Program Executive Office Intelligence, Electronic Warfare and Sensors

(PEO IEW&S), Project Manager Intelligence & Analytics (PM IS&A), Project Linchpin Team in conjunction with Program Executive Office, Simulation Training and Instrumentation (PEO STRI) and

Synthetic Training Environment Cross Functional Team (STE CFT) are issuing this Request For

Information (RFI) as a means of conducting market research to help scope a future contract activity.

1.1. INTRODUCTION

REQUEST FOR INFORMATION ONLY. The purpose of this posting is to notify industry of an RFI.

Project Linchpin enables the Army to deliver trusted solutions for AI-enabled systems through secure

Artificial Intelligence Operations and Artificial Intelligence Services (AIOPs+) while maximizing the

Department of Defense (DoD) and Intelligence Community (IC) investments. Project Linchpin creates a collaborative yet competitive environment of Industry and Government partners to establish the AIOPs+ ecosystem and creates new opportunities for inclusion into the ecosystem through rapid agile acquisition and contracting approaches. The Project Linchpin Team is collaborating with PEO STRI and STE CFT to identify best of breed AI products, solutions, and services to support the implementation of safe, reliable, and ultimately trustworthy AI to enhance Army training and testing operations.

PEO STRI and the STE CFT, both located in Orlando, FL, are key organizations within the US Army, dedicated to modernizing training and simulation capabilities. PEO STRI is the U.S. army acquisition organization chartered to rapidly develop, field, and sustain testing, training and information operations material capabilities to enhance readiness. PEO STRI manages the lifecycle resources of over 260 programs with technology focus on cyber, instrumentation and simulations including spanning Live, Virtual, Constructive, and Gaming domains. The STE CFT, part of the Army Futures Command, focuses on creating a unified and immersive training environment by integrating live, virtual, and constructive training elements, aiming to provide a seamless and realistic training experience for soldiers, regardless of location or platform. Their collaboration is essential in driving innovation to advance the modeling & simulation modernization efforts by accelerating AI adoption to improve combat readiness.

2. DISCLAIMER

THIS IS NOT A NOTICE OF Request for Proposal (RFP) ISSUANCE. Responses to this request are voluntary and will not affect any contractor's ability to submit a proposal if, or when, an RFP is released for a future effort. The requested information is for planning purposes only and does NOT constitute a commitment, implied or otherwise, that a procurement action will be issued. It is issued to invite industry to share their thoughts with the Government on training AI models for Army Programs.

No entitlement to payment by the Government of direct or indirect costs or charges will arise because of the submission of information in response to this request.

Information received will not be considered confidential/proprietary unless marked accordingly.

Company proprietary data will be reviewed by Government employees and authorized representatives only. The Government shall not be liable for or suffer any consequential damages for any improperly identified proprietary information. No award will be made because of this request. This request is for

Simulation Capabilities to Support Army Initiatives.

informational purposes only to promote exchanges of information with industry in accordance with

Federal Acquisition Regulation (FAR) part 15.201. The Government will not pay for any information and/or materials received in response to this request for information and is in no way obligated by the information received.

3. RESPONSE INSTRUCTIONS

Responses related to this Government issued RFI are due no later than 2359 EST on 8 November 2024 in the form of a whitepaper.

Responses shall be sent via email address to: usarmy.apg.peo-iews.mbx.linchpin@army.mil; Subject Line:

“Project Linchpin M&S Capabilities to Support Army Initiatives RFI #6”.

The whitepaper should not exceed 7 pages, not including the cover. The whitepaper must address the following information requests listed below.

The Government is requesting the following information from Industry:

1. Please include the following Company overview information with your response:

a. Company name, NAICS, and CAGE code.

b. Company size and locations.

c. Traditional/non-traditional defense contractor.

d. Point of contact and email address.

2. A narrative that describes how the software solution will:

a. Satisfy each item in the desired capabilities and features listed in paragraph 5.

b. The ability to host the software solution in a virtual environment, to include a commercial cloud or fixed hardware. Please include CPU, GPU, RAM and storage requirements for the solution.

4. BACKGROUND

Modeling and Simulation (M&S) is vital for military training, experimentation, test and evaluation, and acquisition. It replicates real-world operational conditions in a controlled yet realistic environment for safe, cost-effective, and efficient analysis and execution. AI can significantly enhance M&S applications by automating data collection, processing, and analysis. It can rapidly generate adaptive training scenarios and content, optimizing resource allocation that reduces complexity and overhead, providing more Soldier centered insight and mission execution performance, and improve predictive analysis. AI algorithms can learn from data, identify patterns, and make decisions with minimal human intervention, enabling better-informed decision-making, improve training effectiveness, reduce costs, and increased mission readiness in military organizations. These improvements will remove bottlenecks in current M&S systems that require extensive manpower, overhead, and technical footprints to enable future Army readiness.

Using the following example or another example generated by the responding company related to the

M&S portfolio please answer the questions in section 5. Note: this is only one use case of many others that include challenges that pertain to the training, simulation, and instrumentation domain(s).

Simulation Capabilities to Support Army Initiatives.

The Intelligent Observer Controller (IOC) is a system used to support squad-level training exercised. The

IOC is designed to coach, mentor and teach the squad regardless if a human Observer Controller is present. IOC monitors the squad’s actions through sensor data, accounts for mission, enemy, terrain, troops, and time to determine the squad’s proficiency.

The IOC typically consists of a combination of hardware and software components, such as sensors, cameras, and algorithms, that are used to track and monitor the movements and actions of the training participants, squad, and opponent. IOC then determines the tasks that the squad and/or squad members may need additional training.

For example, in a react to direct fire, the squad failed to keep correct distance between squad members while moving. Upon taking enemy fire, the squad did not orientate weapons on the enemy position and failed to keep a continuous volume of suppressive return fire.

Overall, the IOC is a valuable tool for training and preparing soldiers for real-world combat situations, as it provides feedback to the unit commander allowing him to schedule training against performance deficiencies.

5. REQUESTED INFORMATION

1. What is a proposed AI use case: Identify 1 or 2 use cases and provide your approach to turn the use case into a design.

2. Data Collection and Generation: Describe what data is required and your approaches for collecting and/or generating data to support the use case. Include details about data sources, data types, and data quality.

3. Tools for Data Collection, Generation, and Model Training: Please share information regarding any tools and/or platforms recommended for data collection, generation, and model training. Explain how these tools support M&S-related use cases and customers.

4. Models and Frameworks: Describe the types of AI models and frameworks you use or recommend for M&S applications. Explain their strengths, limitations, and suitability for various use cases.

5. Test and Evaluation (T&E): Discuss your approaches to T&E for AI models and systems in the context of M&S. Include information about methodologies, tools, and best practices.

6. Technology Maturity - Technology Readiness Level (TRL): If a specific example, prototype, or solution is referenced, please provide the technology maturity, if applicable please use a TRL number.

7. Skillsets and Labor Categories: Identify the skillsets and labor categories required for the successful implementation and operation of AI solutions in support of M&S. Please consider from the start of the use case definition through integration and deployment.

8. Industry Data and Intellectual Property (IP) Considerations: Share your thoughts on data and

IP sharing, protection, and collaboration within the AI ecosystem for M&S.

9. Cost Models and Licensing Approaches: Provide information about your cost models, licensing approaches, or other pricing structures for AI solutions in support of M&S

10. Counter - Counter AI (CCAI): CCAI is a concept to fortify AI systems against adversarial attacks. By simulating various types of attacks, Counter AI helps identify and mitigate

Simulation Capabilities to Support Army Initiatives.

vulnerabilities within AI models. These simulated attacks can range from data poisoning, where malicious data is injected to corrupt the training process, to evasion attacks, where inputs are subtly altered to deceive the AI into making incorrect predictions.

a. Capabilities and Expertise: What specific types of simulated threats can your company generate (e.g., deep fakes, fake prompts, spoofing attacks)? Please provide examples or case studies of past projects where simulated threats for AI testing were created.

b. Technical Specifications: What technologies and methodologies do you use to create these simulated threats? How do you ensure the realism and effectiveness of the simulated threats?

c. Customization and Flexibility: Can your simulated threats be tailored to specific AI models or applications? How do you handle updates and changes in AI models to ensure ongoing relevance of the simulated threats?

d. Evaluation and Metrics: How do you measure the effectiveness of your simulated threats in testing AI systems? Can you provide metrics or reports that demonstrate the impact of your simulated threats on AI performance?

6. SUMMARY

To address M&S capability needs, Project Linchpin, in partnership with PEO STRI and STE CFT, is requesting information on AI approaches and technologies to bolster the Army's M&S capabilities to improve collective training and readiness. Of particular interest are AI solutions for data collection, generation, model training, and security with models integrated and deployed in various form factors within the tactical environment. The goal is to identify industry capabilities for supporting enterprise model training and fostering collaboration to enhance the AI ecosystem in support of M&S applications.

This RFI is an information-gathering effort to help Project Linchpin, PEO STRI, and STE CFT understand the AI landscape and its potential to strengthen M&S capabilities.

7. QUESTIONS

Questions regarding this announcement shall be submitted in writing by e-mail to usarmy.apg.peo-iews.mbx.linchpin@army.mil; Subject Line: “QUESTIONS: Project Linchpin M&S Capabilities to

Support Army Initiatives RFI #6”. Verbal questions will NOT be accepted. Questions will be answered by posting answers to the https://sam.gov; accordingly, questions shall NOT contain proprietary or classified information. The Government does not guarantee that questions received after 21 October 2024 will be answered. Interested parties are invited to subscribe to the website to ensure they receive any important information updates connected with this RFI.