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FBO DAILY - FEDBIZOPPS ISSUE OF NOVEMBER 18, 2017 FBO #5839
SPECIAL NOTICE

A -- Special Notice for Artificial Intelligence (AI)/Machine Learning (ML) Technology Demonstration - Attachment 1

Notice Date
11/16/2017
 
Notice Type
Special Notice
 
NAICS
541715 — Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
 
Contracting Office
Department of the Army, Army Contracting Command, ACC - APG (W911QX) Adelphi, 2800 POWDER MILL RD, ADELPHI, Maryland, 20783-1197, United States
 
ZIP Code
20783-1197
 
Solicitation Number
W911QX-18-R-0006
 
Point of Contact
Colin Carroll, , Peter Fisher,
 
E-Mail Address
Colin.j.carroll2.mil@mail.mil, Peter.c.fisher4.ctr@mail.mil
(Colin.j.carroll2.mil@mail.mil, Peter.c.fisher4.ctr@mail.mil)
 
Small Business Set-Aside
N/A
 
Description
Attachment 1 (Project Quad Chart Template) Synopsis: The Army Research Laboratory (ARL) Broad Agency Announcement (BAA) for Basic and Applied Scientific Research was recently amended to include a new topic (Artificial Intelligence (AI) and Machine Learning (ML)) under the Information Sciences Campaign. ARL and the Algorithmic Warfare Cross Functional Team (AWCFT) are co-sponsoring a Technology Demonstration to demonstrate and experiment with capabilities related to this new AI/ML topic. ARL invites all businesses engaged in AI/ML development to submit a technology capability package to be designated a sponsored contractor. Overview: The Technology Demonstration provides the opportunity for Special Operations Force (SOF), Department of Defense (DoD), Intelligence Community (IC), & Federal Law Enforcement organizations to collaborate and integrate efforts to produce innovative solutions to tactical, operational, and strategic challenges. It is a truly unique venue providing an opportunity to push systems and concepts to failure in a controlled environment. The Technology Demonstration takes place in Virginia Beach, Virginia, from 30 April 2018 to 10 May 2018. Technology Focus Areas: ARL and the AWCFT are seeking to demonstrate technologies related to AI/ML in the following focus areas: 1) Computer Vision models that enable Geospatial Intelligence processing and exploitation in constrained and unconstrained compute environments through: object identification, object classification, object localization, unique object recognition/recall, object pixel georegistration, object tracking, semantic segmentation, logical expression or semantic description, and activity/situation recognition. 2) New data labeling techniques, tools, and tradecraft for data annotation in support of deep learning: "edge" or "labeling on the line", use of synthetic or photorealistic data, and relabeling/retraining in near-real time. 3) Interfaces for the display, search, and interaction with algorithmically derived metadata and tabular structured algorithmic output: anomaly and pattern of life analysis, object search (visual and metadata), visualization, and fusion with other structured data. 4) Storage and indexing capabilities for local algorithmically-produced data. 5) Language algorithms to process verbal form and written text, including, but not limited to: natural language processing, automated language translation, and sentiment detection. More details on the Artificial Intelligence and Machine Learning topic can be found by searching announcement "W911NF-17-S-0003" at Grants.gov or FBO.gov. Requirements: To be considered, technologies should be able to demonstrate system level capabilities prior to the event. Selected contractors will work with the government sponsor to validate the capability. All sponsored contractors for the event will be required to sign a Non-Disclosure Agreement (NDA) prior to participation. Contractors are responsible for all incurred expenses and sponsored project does not obligate the government for expenses and/or future contracts. The U.S. Government shall not be liable for any costs or expenses for the attendance of this event. Upon formal notice of government project sponsorship, further instructions will be provided. Attendees must be US Citizens. A Secret Collateral security clearance level is required to attend the event. Project submissions can be classified. The government will provide the appropriate data sources and collection platforms during the Technology Demonstration required by the contractor. Submission Instructions: a. Interested parties are requested to respond to this RFI if they have a capability they would like to have considered for participation. b. The expected associated North American Industry Classification System (NAICS) code is 541715 (Research and Development in the Physical, Engineering and Life Sciences - except Nanotechnology and Biotechnology). c. Responses shall be limited to one (1) page executive summary narrative, plus a completed two (2) page power point template (See attachment 1), and submitted via e-mail to Colin.j.carroll2.mil@mail.mil. If you plan to submit a classified response please notify via an unclassified message, so it can be tracked appropriately, and you will be provided instructions for submission. The responses shall be in Microsoft Word and Microsoft PowerPoint compatible format and are due no later than 5:00 PM (local Eastern Time) on Wednesday, 13 December 2017. e. Proprietary information, if any, should be minimized and MUST BE CLEARLY MARKED and completely separated. To help aid ARL, please segregate proprietary information. Be advised that no submissions will be returned. All submissions will be disposed of in accordance with the instructions provided in prospective sources response. If no instructions are listed, ARL will dispose of submissions at their discretion. Additionally, ensure all classifications markings are correct on the submitted responses. f. Responses to this RFI may be evaluated by Government technical experts. The program office 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. Prospective offerors are advised that only Government Contracting Officers are legally authorized to commit the Government. g. The Government will provide the appropriate data sources and collection platforms during the Technology Demonstration required by the contractor. Please list required data types and formats in your response to this notice. Data types could include Electro-optical or Infrared Full Motion Video, Wide Area Motion Imagery, Ground Motion Target Indicator, Synthetic Aperture Radar, Electronic Signals data, etc. Upon contractor selection, the government will provide a library of the required data type to the contractor for use in algorithm training or other technology refinement necessary to demonstrate their capability at this Technology Demonstration. h. The submissions will be evaluated based on their contribution to the AWCFT and the ARL's AI/ML mission as well as the availability of the data sources and collection platforms required by the contractor. i. Upon favorable Government evaluation the company will receive further instructions. No logistical or financial support will be provided to invitees to attend the Technology Demonstration. Note: This notice is being issued for planning and information purposes only. It does not constitute a solicitation, nor is it to be construed as a commitment by the Government. The Government will not pay for any effort expended in responding to the notice, or participation in this event (to include attendees travel costs), nor will the Government accept proposals as a result of this notice. Meals will not be provided at this event. Point of Contact(s): Major Colin Carroll Colin.j.carroll2.mil@mail.mil Peter Fisher Peter.c.fisher4.ctr@mail.mil
 
Web Link
FBO.gov Permalink
(https://www.fbo.gov/notices/30560cb90b31329b9403cacffdc6113e)
 
Record
SN04742594-W 20171118/171116231238-30560cb90b31329b9403cacffdc6113e (fbodaily.com)
 
Source
FedBizOpps Link to This Notice
(may not be valid after Archive Date)

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