NASA FDL: Accelerating Artificial Intelligence Applications in the Space Sciences.
Abstract
NASA has a long history of using Artificial Intelligence (AI) for exploration purposes, however due to the recent explosion of the Machine Learning (ML) field within AI, there are great opportunities for NASA to find expanded benefit. For over two years now, the NASA Frontier Development Lab (FDL) has been at the nexus of bright academic researchers, private sector expertise in AI/ML and NASA scientific problem solving. The FDL hypothesis of improving science results was predicated on three main ideas, faster results could be achieved through sprint methodologies, better results could be achieved through interdisciplinarity, and public-private partnerships could lower costs We present select results obtained during two summer sessions in 2016 and 2017 where the research was focused on topics in planetary defense, space resources and space weather, and utilized variational auto encoders, bayesian optimization, and deep learning techniques like deep, recurrent and residual neural networks. The FDL results demonstrate the power of bridging research disciplines and the potential that AI/ML has for supporting research goals, improving on current methodologies, enabling new discovery and doing so in accelerated timeframes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMIN31A0070P
- Keywords:
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- 1916 Data and information discovery;
- INFORMATICS;
- 1920 Emerging informatics technologies;
- INFORMATICS;
- 1932 High-performance computing;
- INFORMATICS;
- 1998 Workflow;
- INFORMATICS