Notice ID:\u00a0 FA8612-23-R-B003<\/p>\n
This RFI is being issued to determine if there are adequate responsible prospective Contractors, capable of providing an AI\/ML Toolkit for CBC2.<\/p>\n
The Department of the Air Force (DAF) seeks to develop a cross-cutting portfolio of architecture and systems engineering, digital infrastructure, aerial networking, and command and control (C2) software programs for the Advanced Battle Management System (ABMS). The goal of ABMS is to provide foundational capabilities for the DAF BATTLE NETWORK, which is the DAF\u2019s systems of systems fusing sensors, effectors, and sustainment grids for decision advantage. The DAF BATTLE NETWORK is the DAF\u2019s primary contribution to the Combined Joint All Domain Command and Control (CJADC2) joint warfighting concept.<\/p>\n
Within the portfolio\u2019s software and applications thrust area, ABMS seeks to apply advanced automation, artificial intelligence and machine learning technologies across the integrated portfolio of BMC2 capabilities. The SOO, attached to this posting, aims to outline the capability needs, technology requirements and expertise needed to improve reaction time across the \u201cSense, Make Sense, Act\u201d C2 paradigm. This effort is identified as a \u201ctoolkit\u201d to emphasize that there is no once-size-fits-all AI\/ML solution. Many types of AI applications exist for various problem and opportunity spaces \u2013 this SOO intends to identify several opportunity spaces but is not limiting the performer (or effort) to those specific technology applications. This effort shall be a collection of tools and technologies that improve tactical C2 software applications under development within multiple programs (e.g., Cloud-Based Command and Control) and reduce operational workflow timelines for C2. The DAF is seeking information to gain an in-depth knowledge of state-of-the-art commercialized artificial intelligence and automation technologies in a variety of mission applications to include data collection and curation, machine to machine operations, large language models, and continuous and\/or reinforced learning training models \u2026<\/p>\n