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This Government Contract opportunity from Department Of Defense was posted on June 15, 2023. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Artificial Intelligence and Machine Learning Research for Expeditionary Maneuver and Air/Ground Reconnaissance

Closed
W911QX-23-R-0037Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

General Info

NAICS

N/A

Place of Performance

MD

Set-Aside

NONE

Documents

0

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Timeline

PhaseClosed
Posted

special-notice

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyDepartment Of Defense → W6QK Acc-Apg Adelphi
Contacts1 person available
OfficeADELPHI, MD, 20783-1197, USA
Office AddressADELPHI, MD, 20783-1197, USA

Full Description

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Special Notice - Artificial Intelligence and Machine Learning Research for Expeditionary Maneuver and Air/Ground Reconnaissance General Information Document Type: Special Notice Notice Number: W911QX-23-R-0037 Posted Date: 15 June 2023 Category: Research and Development Set Aside: N/A Contracting Office Address Department of the Army, Army Contracting Command, ACC - APG (W911QX) Adelphi, 2800 Powder Mill Road, Building 601, Adelphi, Maryland, 20783-1197, United States Description This special notice references the ARL BAA which can be found at Grants.gov or FBO.gov document: W911NF-23-S-0001. Synopsis: The Army Research Laboratory (ARL) is planning to consider proposed research and development solutions submitted under the ARL Broad Agency Announcement (BAA) topic ARL-BAA-0039, - Artificial Intelligence (AI) and Machine Learning (ML) Managing Massive Data Sets, in support of new technologies and research-based approaches in the area of Highly Modular AI/ML Pipelines for AI Assurance. Problem: As the Army looks to invest in A I / M L pipelines to support the Soldier two key concerns will be developing AI/ML pipelines that are more modular, and that can provide AI Assurance. Current ML pipelines provide limited modularity and are prone to prohibitively high costs to change out individual modules in the pipeline. In addition, they are vulnerable to manipulation of code, data, labels, and labeling processes that may compromise downstream ML models. Specific areas of interest are: - Identification of proposed standards to address these problems based on the principles of Traceability, Observability, Replaceability, and Consumability (TOR-C). - Containerized methods for enforcing TOR-C standards within a machine learning pipeline. - Improved methods for transparency and assurance of code, data, labels, and labeling processes. - Telemetry capabilities to better observe and track data and information within individual modules of a machine learning pipeline. Innovative research solutions are sought in the area described above under section ARL-BAA-0039 of the ARL BAA. It is anticipated that initial awards resulting from responses to this Special Notice will be made in FY23. Awards are expected to have a 6 month period of performance and, depending on proposals submitted, additional option years may be included in the final award. However, the total proposed period of performance including options may not be more than five (5) years. To be considered for an invitation to submit a proposal, applicants must comply with the submission instructions included in the ARL BAA. Whitepaper Content and Submission - This section further defines section A.1 of the BAA. Contract Proposals in the ARL BAA for purposes of this special notice only. 1. Content: Whitepapers submitted in response to this announcement shall contain the following content: a. COVER PAGE (not to exceed one (1) page): i. The whitepaper cover page shall include at a minimum: ii. Title of the whitepaper iii. Name of the organization submitting the whitepaper iv. Names of any participating organizations v. CAGE Code of the organization submitting the whitepaper vi. Name, address, email, phone # of the applicant's POC b. TECHNICAL CONTENT (not to exceed five (5) pages): i. A not to exceed 150 word executive summary of the proposed effort and its contribution to the Army's mission. ii. A detailed discussion of the effort's scientific research objective, approach, relationship to similar research, facilities and infrastructure, and level of effort shall be submitted. Also include the nature and extent of the anticipated results and, if known, the manner in which the work will contribute to the accomplishment of the Army's mission and how this contribution would be demonstrated. iii. Summary of the applicant's key research facilities, instrumentation, key teaming agreements and related resources. iv. The type of support, if any, the applicant requests of the Government, such as facilities, equipment, demonstration sites, test ranges, software, personnel or materials, shall be identified as government furnished equipment (GFE), government furnished information (GFI), government furnished property (GFP), or government furnished data (GFD). Applicants shall indicate any Government coordination that may be required for obtaining equipment or facilities necessary to perform any simulations or exercises that would demonstrate the proposed capability. v. The cost portion of the whitepaper must contain a brief cost estimate revealing all the component parts of the proposal, including research hours, burden, material costs, travel, etc. Any cost sharing or other applicant contributions should be included. c. ADDENDUM (not to exceed one page): Include biographical sketches of the key personnel who will perform the research, highlighting their qualifications and experience. 2. Format: Whitepapers must be in the following format but do not require any special forms: a. All submissions must be UNCLASSIFIED b. Layout i. Page Size: 8 - x 11 inches ii. Margins - 1 inch iii. Spacing - single iv. Font - Times New Roman, 12 point 3. Whitepapers submitted under this special notice will be evaluated by Government experts. During this evaluation, contractor technical personnel may provide technical expertise to the Government. The Government has contracted for various non-government scientific, engineering, technical and administrative staff support services, some of which require contractors to obtain access to proprietary information submitted by other contractors. All non-government contractor support personnel have signed and are bound by appropriate non-disclosure agreements and organizational conflict of interest statements. 4. Disposition of submissions: No submissions will be returned. All submissions will be disposed of in accordance with the instructions provided in an applicant's whitepaper. If no instructions are listed, ARL will dispose of submissions at their discretion. 5. Deadline: All whitepapers are due no later than 5:00 PM EST, 30 June 2023, to be considered for a FY23 award. A whitepaper sent by any other means (e.g., hand-carried, postal service mail, commercial carrier or fax) will not be considered. Whitepapers received after the deadline will not evaluated for an FY 23 award. Pages submitted in excess of the page counts specified above will not be evaluated. 6. Applicants submitting whitepapers are cautioned that only a Contracting Officer/Grants Officer/Agreements Officer can obligate the Government to any legal instrument involving expenditure of Government funds. All inquiries regarding this special notice shall be submitted in email to the address below. 7. The Government will not pay for any effort expended in responding to this special notice. Questions: Any questions prior to whitepaper submission must be submitted to the point of contact below and not to any of the technical POCs included in the ARL BAA. Original Point of Contact: Questions regarding this announcement must be sent to the following email address: Brent.j.lance.civ@army.mil Whitepaper submission should be sent to the following email address: Brent.j.lance.civ@army.mil

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