SOURCES SOUGHT
70 -- Request for Information (RFI) for Artificial Intelligence/Machine Learning
- Notice Date
- 4/14/2021 12:57:06 PM
- Notice Type
- Sources Sought
- NAICS
- 511210
— Software Publishers
- Contracting Office
- W6QK ACC-APG ABERDEEN PROVING GROU MD 21005-1846 USA
- ZIP Code
- 21005-1846
- Solicitation Number
- AI_ML_2021
- Response Due
- 5/14/2021 6:00:00 AM
- Archive Date
- 05/29/2021
- Point of Contact
- Sabrinna Cosom, Dr. Bridgette Latimer
- E-Mail Address
-
sabrinna.r.cosom.civ@mail.mil, Bridgette.a.latimer@civ.mail.mil
(sabrinna.r.cosom.civ@mail.mil, Bridgette.a.latimer@civ.mail.mil)
- Description
- The Army Contracting Command on behalf of Project Manager Intelligences Systems & Analytics (PM IS&A) is issuing this RFI as a means of conducting market research to identify potential sources having interest and industry technologies available to support/provide Artificial Intelligence/Machine Learning solutions. The result of this market research will contribute to determining the method of procurement, if a requirement materializes. Based on the responses to this sources sought notice/market research, this requirement may be set-aside for small businesses (in full or in part) or procured through full and open competition. Multiple awards may be made. All small business set-aside categories will be considered. Telephone inquiries will not be accepted or acknowledged, and no feedback or evaluations will be provided to companies regarding submissions. General Information: Currently there is not an incumbent performing this work. DISCLAIMER THIS REQUEST FOR INFORMATION IS FOR INFORMATIONAL PURPOSES ONLY. THIS IS NOT A REQUEST FOR PROPOSAL TO BE SUBMITTED. IT DOES NOT CONSTITUTE A SOLICITATION AND SHALL NOT BE CONSTRUED AS A COMMITMENT BY THE GOVERNMENT. RESPONSES IN ANY FORM ARE NOT OFFERS AND THE GOVERNMENT IS UNDER NO OBLIGATION TO AWARD A CONTRACT AS A RESULT OF THIS ANNOUNCEMENT. NO FUNDS ARE AVAILABLE TO PAY FOR PREPARATION OF RESPONSES TO THIS ANNOUNCEMENT. ANY INFORMATION SUBMITTED BY RESPONDENTS TO THIS TECHNICAL DESCRIPTION IS STRICTLY VOLUNTARY. INTRODUCTION PM IS&A is looking for the best-of-breed in AI/ML models.� Responders are requested to provide information in the following areas: models, data, processes/tools, security, and company/cost details.� �The findings from this market research will help PM IS&A tailor its acquisition strategy and ensure that AI/ML is seamlessly integrated into major programs and efforts such as Tactical Intelligence Targeting Access Node (TITAN) and Intelligence Applications (Intel Apps).�� The findings will also help PM IS&A to identify companies who are developing AI/ML models that address the U.S. Army�s critical technology gaps.�� BACKGROUND The U. S. Army is investing significant resources into advancing its intelligence and warfighting capabilities.� The sheer volume, velocity, veracity, and variety of data has forced the US Army to reassess its intelligence and warfighting operations.� Also, our adversaries, Tactics, Techniques, and Procedures have become increasingly sophisticated and require the U. S. Army to accelerate its modernization efforts.�� In response, the Artificial Intelligence (AI) Task Force was established.� The AI Task Force identified AI and Machine Learning (ML) as one of the Army�s key enabling technologies for modernizing and advancing its operations.�� Three key areas where AI/ML have been identified are decreasing the cognitive burden on analysts, increasing mission effectiveness, and providing timely information to decision makers.� Examples of increasing mission effectiveness range from enabling Long Range Precision Fires and Large Scale Combat Operations to identifying specific targets with a high confidence in real time or near real time.� The future of warfare is characterized as faster and at longer ranges, is more destructive, targets civilians and military equally across the physical, cognitive, and moral dimensions.� To succeed in such scenarios, the ability to provide accurate and timely intelligence is critical to intelligence analysts, warfighters and decision makers. �� In response to these challenges and threats, The United States Army is replacing its legacy systems with brand new state of the art systems and capabilities.� PM IS&A is leading the effort to modernize the Army�s intelligence systems.� The modernization efforts are far reaching and include a new data warehousing capability, new ground station, and new software baseline.� The new data warehousing capability will include data ingress, cleansing, processing, egress, and querying to enable storage and timely processing, exploitation and dissemination of intelligence data. In addition, the ground station modernization program known as TITAN will leverage modern networking technologies and data frameworks that enable data discovery, data exchange, and the use of AI/ML applications and software that improves reporting timeliness and accuracy to support Large Scale Combat Operations in connected, Disconnected Intermittent Limited and Anti Access/Area Denial environments. The near term focus is on incorporating current (and future) sensors from National, Joint, Commercial and Army sensors and platforms, while working to minimize risk to identified capability gaps and future system integration efforts. TITAN may leverage an AI/ML pipeline known as Arcane Fire for model training, management, and deployment of AI/ML models.� It will also have its own model testing and evaluation suite and a repository of models.� Finally, Intel Apps will provide leap ahead software capability in support of the Multi-Domain Intelligence Framework, and Multi-Domain Operations by enabling intelligence professionals to work through the intelligence cycle with increased speed, precision and accuracy. Intel Apps is the next generation of the Army Intelligence software functions and capabilities that will replace select legacy capabilities in the Command Post Computing Environment with leap ahead capabilities over time.� Collectively, these systems will provide state of the art processing, exploitation, and dissemination capabilities to intelligence analysts for multiple intelligence domains (SIGINT, GEOINT, IMINT, All Source, etc.) In addition, these capabilities will be deployed at major fixed sites, CORPs, Division, and Brigade and on various security classification networks (SIPRNET, JWICS.) � QUESTIONS TO INDUSTY Please address the questions in 10 pages or less.� Also complete Table 1 in the Appendix section to provide detailed information on your AI/ML models.��� AI/ML Models Have you developed or are you developing (within the next 12 months) any AI/ML models?� Please refer to Table 1 in Appendix for specifics and desired format for responses.� � What explainability measures are applied to existing algorithms to increase model trust by the user? Do you have any associated metrics on your models (e.g. runtime/instances, complexity level of trained capability, number of positive detects, etc�)? Intellectual Property Rights (i.e. Data Rights) What will be the Government�s license rights for the training data (annotated), data (or data set) produced by the model, learned/modified/trained hyper-parameters or model-weights, and any technical data or software? Who provides the data and how much is needed and what are the implications? Example scenarios are provided below. Government provides little to no data (i.e. model meets our expectations already) Government provides all or most of the data Processes/Tools/Standards What is your end to end process for AI/ML from development to deployment? What software tools are you currently using? What AI/ML standards have you implemented? What AI/ML standards are you currently using? Please review the Arcane Fire standards and provide feedback on them.� The standards are located in the Appendix section of this document.������ ����� Can you comply with these standards? If not, please explain why.� Are there other standards that we should consider to meet our open modular goals? Hardware What type of hardware have you deployed the models on? Are you currently investigating any hardware solutions to optimize performance? Security If your model accepts classified data as its input, can you provide any supporting security documentation? What anti spoof measures are applied to existing algorithms (if any)? Company/Cost Details What is your company�s business model? � What is your revenue model, market segment, vision statement, value proposition, etc.? Do you develop models from scratch and/or tailor existing models? What licensing options do you offer for a model that is built partially or entirely with government data? What are the associated Intellectual property protections? What are the associated costs for the various options for both using, tuning, training, and re-training the model (identify any assumptions needed)? What are your preferred contracting vehicles and types (e.g. fixed price, cost plus, OTA, IDIQ, etc.)? Do you have any prototypes currently in development, whitepapers, demos,� product roadmaps, or case studies that you can share? What is the timeline associated with any planned development and deployment efforts? Electronic submissions are due no later than 0900 on May 14, 2021.� Responses should be submitted via e-mail to Dr. Bridgette Latimer, Bridgette.a.latimer@civ.mail.mil and Mrs. Sabrinna Cosom, Sabrinna.cosom.civ@mail.mil.� Questions regarding the requested material may also be sent via email prior to the due date. Proprietary information, if any, should be minimized and MUST BE CLEARLY MARKED.� To aid the Government, please segregate proprietary information.� Please be advised that all submissions become Government property and will not be returned. NON-DISCLOSURE AGREEMENT (NDA) RFI respondents are informed that MITRE a Federally Funded Research and Development Center (FFRDC) may assist the Government with its market research. These individuals will be authorized access to the RFI responses to enable them to perform their respective duties. The FFRDC will be prohibited from competing on a future related acquisition.� The Government will use the information submitted in response to this notice at its discretion and will not provide comments to any submission; however, the Government reserves the right to contact any respondent to this notice for the sole purpose of enhancing understanding of the notice submission. All data received in response to this Sources Sought that is marked or designated as corporate or proprietary will be fully protected from any release outside the Government. Company proprietary data will be reviewed by Government employees and authorized representatives only.�
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