supply chain management, logistics coordination, target identifications and simulation
The objective of this SBIR topic is to advance methods for generating and labeling synthetic data representing various classes of Radio Frequency (RF) signals. This synthetic data will support the training of Electronic Support and Signals Intelligence (SIGINT) models aimed at enhancing automated detection, characterization, and identification (DCI) of Signals of Interest (SoI).
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.
Large Language Model Course of Action Analysis Read More »
The proposed SBIR topic aims to advance the capabilities of large language models by addressing critical challenges and enhancing functionalities relevant to military applications, particularly within the U.S. Army.
Dynamic Generative Large Language Model for Continuous Situational Awareness Read More »
To equip artisans with technology that enhances operational capabilities, their breadth of logistical support, and property accountability. Proposals should allow for the flexibility of artisans to respond to mixed model production and innovations that enable artisans to execute ergonomically challenging tasks. There is a need for technologies that equip artisans with standard yet flexible enduring technologies to sustain air missile defense and power generation systems, ensuring that assets are returned to combat swiftly.
Shop Tools and Enablers Open Topic Read More »
This open topic accepts both Phase I and Direct to Phase II submissions. Phase I proposals are accepted for a cost up to $250,000 for a 6-month period of performance and Direct to Phase II proposals are accepted for a cost up to $2,000,000 for a 24-month period of performance. All submissions most address the following 6 AI sub-fields: Synthetic data generation in a format applicable to a given situation that is not obtained by direct measurement. This includes visual, textual, video, geospatial, and sensor data.
Artificial Intelligence/ Machine Learning (AI/ML) Focused Open Topic Read More »
This Army SBIR solicitation is for artificial intelligence and machine learning-driven methodologies that can control the production processes for Nano-Nitramines. The Army seeks to produce the most efficient, effective formulations currently known in an agile and flexible manner. AI/ML-driven manufacturing and formulation science can apply “cradle to grave” for Nano-Nitramines, and can enable their widespread adoption by making research and production automated.
AI-Driven Production of Coarse- and Nano-Nitramines Read More »
This Army SBIR project will develop field-level maintenance and repair of weapon systems electronics that shorten supply chain latency for electronic component repairs. The solution must screen electronic components for no evidence of failure at the source in the tactical unit.
AI-Enhanced TPS Development and Sustainment Read More »
With the increasing availability of digital imagery, including satellite data for electro-optical/infrared, synthetic aperture radar and full-motion video, there is a growing need for automated methods to efficiently process and analyze vast amounts of multi-modal data.
Robust Computer Vision for Better Object Detection with Limited Training Data Read More »
The Army needs a technology that can completely characterize an optic under test via phase recovery and a collimated, partially-coherent light source.
Zernike Polynomials via Phase Recovery Read More »
Starting with how the U.S. Army develops Acquisition Requirements Packages, small businesses must develop and deliver a state-of-art, artificial intelligence and machine learning-enabled system to modernize and automate Army acquisition processes.
AI-Enabled ARP, Select and Monitor Read More »
