Artificial Intelligence/Machine Learning, ASA(ALT), Direct to Phase II
Large Language Model Course of Action Analysis
Objective
The objective of this research topic is to explore Boyd’s Observe, Orient, Decide and Act Loop with the goal of finding disruptive courses of action in a multi-domain environment that allow warfighters to impact both the rate of engagement with a competitor, but also the rhythm of engagement that allow our commanders and warfighters to leverage both the complexity and dynamism inherent in a multi-domain operation to create decisive wins through strategic surprise.
Description
This topic will accept Direct to Phase II submission only. DP2 proposals are accepted for a cost up to $2 million for an 18-month period of performance.
This research will enable intelligent process automation for the warfighter mission areas of mission command and intelligence with the objective of sorting Open-Source data and Publicly Available Information to find and enrich actionable information.
Phase I
Proposers interested in submitting a DP2 proposal must provide documentation to substantiate that the scientific and technical merit and feasibility equivalent to a Phase I project has been met. Documentation can include data, reports, specific measurements, success criteria of a prototype, etc.
Phase II
Produce prototype solutions that will be practical and feasible to operate in edge and austere environments. Companies will provide a technology transition and commercialization plan for Department of Defense and commercial markets.
The Army will evaluate each product in a realistic field environment and provide solutions to stakeholders for further evaluation. Based on Soldier field evaluations, companies will be requested to update the previously delivered prototypes to meet final design configuration.
DP2 Submission Materials
- 10-page technical volume for down-select.
- 5-page feasibility documentation, showing how technical feasibility has already been achieved.
- 8-slide commercialization plan; template provided in announcement.
- “Statement of Work” outlining intermediate and final anticipated deliverables during the Phase II award period.
Phase III
- LLM COAA technology is encompassed by the broader space of Situational Awareness. Situational Awareness solutions play a crucial role in enabling real-time decision-making, risk mitigation, and operational efficiency in complex environments.
- Development of COAs in military operations is traditionally a time-consuming process. COA-GPT is a novel algorithm employing LLMs for rapid and efficient generation of military plans that address planning discrepancies and capitalize on emergent windows of opportunity.
- Military/Defense applications of open-source data and publicly available information (OS/PAI) utilized in COAA LLMs for U.S. Special Operation Forces include:
- Data fusion for Advanced Situational Awareness.
- Geospatial Pattern Analysis and Self-Location in GPS-Denied Environments (celestial imagery to enable self-location without GPS for ground operators using ATAK).
- Indicators and Warnings: examine tactical, operational, and strategic variables across the operational environment.
- Dual-use applications include:
- Autonomous systems (Unmanned Aerial Systems /drones).
- Smart cities/homes.
- Internet of Things sensors for home and business.
- Predictive analytics for climate and energy applications.
- Disaster management.
Submission Information
For more information, and to submit your full proposal package, visit the DSIP Portal.
SBIR|STTR Help Desk: usarmy.sbirsttr@army.mil
References:
- https://ieeexplore.ieee.org/abstract/document/9384519
- https://www.hindawi.com/journals/ijis/2023/8676366/
- https://www.mdpi.com/2227-7390/10/9/1397
- KEYWORDS: LLM, Large Language Model, AI/ML, Courses of Action, COA
Objective
The objective of this research topic is to explore Boyd’s Observe, Orient, Decide and Act Loop with the goal of finding disruptive courses of action in a multi-domain environment that allow warfighters to impact both the rate of engagement with a competitor, but also the rhythm of engagement that allow our commanders and warfighters to leverage both the complexity and dynamism inherent in a multi-domain operation to create decisive wins through strategic surprise.
Description
This topic will accept Direct to Phase II submission only. DP2 proposals are accepted for a cost up to $2 million for an 18-month period of performance.
This research will enable intelligent process automation for the warfighter mission areas of mission command and intelligence with the objective of sorting Open-Source data and Publicly Available Information to find and enrich actionable information.
Phase I
Proposers interested in submitting a DP2 proposal must provide documentation to substantiate that the scientific and technical merit and feasibility equivalent to a Phase I project has been met. Documentation can include data, reports, specific measurements, success criteria of a prototype, etc.
Phase II
Produce prototype solutions that will be practical and feasible to operate in edge and austere environments. Companies will provide a technology transition and commercialization plan for Department of Defense and commercial markets.
The Army will evaluate each product in a realistic field environment and provide solutions to stakeholders for further evaluation. Based on Soldier field evaluations, companies will be requested to update the previously delivered prototypes to meet final design configuration.
DP2 Submission Materials
- 10-page technical volume for down-select.
- 5-page feasibility documentation, showing how technical feasibility has already been achieved.
- 8-slide commercialization plan; template provided in announcement.
- “Statement of Work” outlining intermediate and final anticipated deliverables during the Phase II award period.
Phase III
- LLM COAA technology is encompassed by the broader space of Situational Awareness. Situational Awareness solutions play a crucial role in enabling real-time decision-making, risk mitigation, and operational efficiency in complex environments.
- Development of COAs in military operations is traditionally a time-consuming process. COA-GPT is a novel algorithm employing LLMs for rapid and efficient generation of military plans that address planning discrepancies and capitalize on emergent windows of opportunity.
- Military/Defense applications of open-source data and publicly available information (OS/PAI) utilized in COAA LLMs for U.S. Special Operation Forces include:
- Data fusion for Advanced Situational Awareness.
- Geospatial Pattern Analysis and Self-Location in GPS-Denied Environments (celestial imagery to enable self-location without GPS for ground operators using ATAK).
- Indicators and Warnings: examine tactical, operational, and strategic variables across the operational environment.
- Dual-use applications include:
- Autonomous systems (Unmanned Aerial Systems /drones).
- Smart cities/homes.
- Internet of Things sensors for home and business.
- Predictive analytics for climate and energy applications.
- Disaster management.
Submission Information
For more information, and to submit your full proposal package, visit the DSIP Portal.
SBIR|STTR Help Desk: usarmy.sbirsttr@army.mil
References:
- https://ieeexplore.ieee.org/abstract/document/9384519
- https://www.hindawi.com/journals/ijis/2023/8676366/
- https://www.mdpi.com/2227-7390/10/9/1397
- KEYWORDS: LLM, Large Language Model, AI/ML, Courses of Action, COA