Inactive

REQUEST FOR INFORMATION: THIS IS NOT A SOLICITATION; The Government is not obligated to make an award as a result of this request. This Request for Information (RFI) is for informational purposes only... REQUEST FOR INFORMATION: THIS IS NOT A SOLICITATION; The Government is not obligated to make an award as a result of this request. This Request for Information (RFI) is for informational purposes only; this is not a Request for Proposal (RFP). The Government will not pay for information and materials received in response to this RFI and is in no way obligated by the information received. The information the Government receives in response to this RFI will be discussed and assessed by U.S. Army Combat Capabilities Development Command (DEVCOM), Command, Control, Computers, Communications, Cyber, Intelligence, Surveillance, and Reconnaissance Center (C5ISR Center) Research & Technology Integration Directorate and other Government agencies. All proprietary or competition sensitive information should be clearly marked for proper protection. Additionally, the Government may use the information provided to develop a future Performance Work Statement, Statement of Objectives and/or Performance Based Specification(s). BACKGROUND/DESCRIPTION: The United States Army C5ISR Center is issuing this RFI to determine the state-of-the-art and state-of-industry in synthetic data for training Aided Target Recognition (AiTR) algorithms. In today’s Army, artificial intelligence (AI) based systems are a key component of the future fighting force. These systems will be required to quicken our ability to find, track and action adversary targets. AiTR algorithms are a key component of these systems. A critical factor of these algorithms is the reliance on vast amounts of data needed to train them. One approach to solving this data problem is by using synthetic data to train, or partially train, these algorithms. Synthetic data, as a solution for AiTR model training, has a number of advantages to include a near-infinite supply of data, ability to create data of scarce targets, and limitless ability to model a wide range of environments. C5ISR Center is seeking information on solutions to generate synthetic data for AiTR model training. Solutions of all maturity are being sought from vendors with an interest in developing, maturing, and/or productizing their solution for use in Army systems. WHITE PAPER SUBMISSION REQUIREMENTS: C5ISR Center asks interested and capable sources to submit a white paper containing a description of your solution. Responses shall be limited to 25 single-sided pages (excluding cover page, table of contents, and acronym listing pages), minimum 10 pt. New Times Roman font. All responses to this RFI shall be submitted to Arlene Wadkins, mildred.a.wadkins.civ@mail.mil no later than 13 September 2021. QUESTIONS TO THIS ANNOUNCEMENT: All questions regarding this announcement are due no later than five business days before the close of this announcement. The Government makes no guarantee of responding timely but will answer on a best-effort basis. Therefore, the Government recommends that respondents submit questions early in the process. Respondents should clearly mark any questions or material related to communications regarding this RFI as proprietary if content warrants such a claim. If the Government has additional questions or requires information after reviewing respondents’ responses, the Government may contact the respondent directly. Therefore, please indicate a technical point of contact and associated contact information. Following evaluation of your response, the government may request a follow-up briefing to discuss your proposed solution. RESPONSE REQUIREMENTS: Each respondent’s white paper must provide, at a minimum, sufficient information to answer the below questions in response to this RFI. In addition, please provide any other relevant information needed to fully understand and assess your capability, including, but not limited to, a brief synopsis of current and past relevant activities in AI development, maturation, integration, and/or productization. Respondent’s name and type of entity (e.g., academia, UARC, FFRDC, small business, etc.). How many full-time employees do you have? How many years have you been contracting with the Department of Defense or intelligence community? Do you have any active contracts with the Army? (Please note, this question will not be used to qualify a potential offeror. This information is only requested for background information.) Please provide the names of your relevant products/capabilities with an accompanying high-level description of the products and/or capabilities. For each listed product or capability, please describe its maturity and provide sufficient details to substantiate your assessment. Where possible, please provide an estimated Technology Readiness Level (TRL) (https://acqnotes.com/acqnote/tasks/technology-readiness-level) with justification. Describe, in as much detail as possible, examples, if they exist, of where your product or capability has been used in a production environment or demonstration/experiment as part of an integrated system. Who owns the technical data to your product(s)? What data rights would you assert? Are you willing to share details of your product with Government subject matter experts (SMEs) in order to further validate the capabilities and limitations of your product? Have you provided your products or capabilities to another public or private entity for third-party use? If yes, what was the business model you used for that engagement? What business model(s) are you open to using if you were to contract with the Army (e.g., licensed software, per dataset fee, Government-owned software, etc.)? Describe the capabilities and limitations of your technology, as it exists today and your plan to expand the capability in the future. Please include explicit and specific details on what imaging bands you can simulate or support (e.g., Electro-Optics (EO), Shortwave Infrared (SWIR), Midwave Infrared (MWIR), Longwave Infrared (LWIR)) and types of image parameters you can simulate or support (e.g., targets, clutter, background, environmental factors, lighting conditions). Discuss the work you have done to validate that your capability generates synthetic data effective for AiTR model training (i.e., how do you know your solution is a good one?). Give details on your validation process/testing and include results to the level necessary to prove your current capabilities (i.e., how do we know your solution is a good one and/or confirm your results?). Provide, to the greatest extent possible, a thorough description of your technical solution/ approach to solving the problem of generating synthetic data for AiTR algorithm training. Be sure to list any other tools, models, and/or dependencies that are used/required in your capability (e.g., Modtran). Give enough information to allow the Government to assess how unique and novel your solution is compared to existing state-of-the-art technology. Would you be interested in and willing to demonstrate your capability to the Government via a Cooperative Research and Development Agreement (CRADA) with the Government? This demonstration would be at no cost to the Government, but Government SMEs would provide feedback based on their assessment, if so desired. The data received in response to this RFI is for informational purposes only and does not mandate or impose requirements. The Government desires respondents to provide data in its response without restrictions on its use. However, the Government recognizes that proprietary data may be included with your response. If so, clearly mark all proprietary information.