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Ada Phase I

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC20C0634
Agency Tracking Number: 204665
Amount: $124,809.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: T11
Solicitation Number: STTR_20_P1
Timeline
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-08-27
Award End Date (Contract End Date): 2021-09-30
Small Business Information
3600 Green Court, Suite 600
Ann Arbor, MI 48105-2588
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jeremiah Folsom-Kovarik
 (407) 602-6116
 jeremiah.folsom-kovarik@soartech.com
Business Contact
 Wendy Hodel
Phone: (734) 887-7632
Email: wendy.hodel@soartech.com
Research Institution
 Georgia Tech Research Institute (GTRI)
 
205 14th Street NW
Atlanta, GA 30318-5303
United States

 Nonprofit College or University
Abstract

Soar Technology, Inc. (SoarTech) and Georgia Tech Research Institute (GTRI) will research and develop a digital assistant (quot;Adaquot;) that can help NASA experts search for and effectively use scientific and technical information (STI) in their work. Ada can provide cognitive support in high-effort search tasks, like examining details of more sources, and use tasks, like applying search results to produce a work product.Our team has already created a search tool to help examine and use STI in complex information environments, which will enable us to quickly prototype a digital assistant with search at its center. We propose to transform the search tool into a digital assistant by adding NASA-specific knowledge structures, tailored user interactions that make relevant details within STI accessible, and cognitive support dialogs to help users accomplish work. The increased interactivity and self-improvement are key to make Ada into a research partner rather than a tool.Enhancing search with cognitive support functions is made possible by innovative machine intelligence -- cognitive modeling that reasons about tasks and user needs, as well as structured machine learning (ML) that uses symbolic knowledge structures to make deep learning more efficient and accurate. The proposal team have worked together and in parallel on related science and technology, allowing Ada to leverage millions of dollars in funded research progress.Our proposed Phase I research will produce a software prototype that helps examine and use search results, a demonstration of structured ML feasibility, and designs for adding new interactivity and cognitive support. Phase II will implement, deploy, and test a full digital assistant that can build on the knowledge in search products to help the user accomplish a work task with interactive, tailored cognitive support.

* Information listed above is at the time of submission. *

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