Due date delay for Application of Artificial Intelligence/Machine Learning Tools for NASA Science (RFI)

Due date delay for Application of Artificial Intelligence/Machine Learning Tools for NASA Science (RFI)

Status Report
From: NASA HQ
Posted: Wednesday, November 6, 2019

NOTICE: Amended November 6, 2019. This amendment delays the due date for the request for information to this program element in order to provide the community with more time to respond. The due date has been extended to November 14, 2019.  

Request for Information: Application of Artificial Intelligence/Machine Learning Tools to NASA Science

Solicitation: NNH20ZDA002L

Background:

FDL is an applied artificial intelligence (AI) research accelerator leveraging the newest developments in AI and Machine Learning (ML) technologies from academia and the private sector and applying them to challenges relevant to NASA’s goals in space and earth sciences. Teams of computer scientists and space and earth scientists work to solve problems important to NASA and humanity’s future within a given time frame. Each team is made up of four participants (two computer scientists and two domain scientists). The teams are mentored by subject matter experts (SMEs) in both science domains and AI/ML. FDL is a public-private partnership between NASA and the SETI Institute, commercial and academic institutions and other foreign and domestic agencies.

How to respond to this RFI:

Submissions shall be as a Notice of Intent (NOI) via the NSPIRES page for Request for Information: Application of Artificial Intelligence/Machine Learning Tools to NASA Science NNH20ZDA002L. Responses to this RFI by other means will not be accepted. 

When creating the NOI in NSPIRES one will supply identifying information and be prompted to provide a summary and answer five short ‘questions’ by filling in text boxes, all of which are limited to 4000 characters. For more information please read the text of the FDL RFI on NSPIRES.

Points of Contact:

Questions concerning this Request for Information may be emailed to Madhulika Guhathakurta at madhulika.guhathakurta@nasa.gov and Michael Seablom at michael.s.seablom@nasa.gov.

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