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dc.date.accessioned2022-11-10T21:17:47Z
dc.date.available2022-11-10T21:17:47Z
dc.date.issued2022-11-10
dc.identifier.urihttps://hdl.handle.net/1721.1/146347
dc.description.abstractTwo teams involving Laboratory staff were recognized with 2020 awards from the Department of the Air Force (DAF)−MIT Artificial Intelligence (AI) Accelerator. Recipients were selected from more than 150 airmen, researchers, faculty, and students from the DAF, the Laboratory, and MIT who are part of a collaborative effort to accelerate fundamental advances in AI. The AIA Director's Award, which highlights "excellence and impact with a focus on collaboration across the AIA and with stakeholders," recognized the Earth Intelligence Engine (EIE) project team for "cross-organizational collaboration, curation of novel datasets, visualization of forecasts, and delivery of an innovative challenge problem." The Earth Intelligence Engine (EIE) project targets three research areas — the earth intelligence platform, earth intelligence enhancement, and earth visual models — to build weather and climate resiliency for the U.S. Air Force. Resiliency against hurricanes, wildfires, flooding, sea level rise, and other extreme-weather and climate related threats is critical to protecting USAF resources such as military bases and ensuring mission readiness. The AIA Challenge Award recognized the Puckboard project team for designing and implementing two community challenge problems focused on aircrew scheduling. Puckboard is a web-based software application for scheduling pilots and loadmasters—personnel responsible for loading and unloading cargo and passengers—to mission and training flights.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesThe Bulletin;
dc.rightsAttribution-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/*
dc.subjectAIAen_US
dc.subjectMIT Lincoln Laboratoryen_US
dc.subjectAIAen_US
dc.subjectLLSCen_US
dc.subjectArtificial Intelligenceen_US
dc.titleTwo Laboratory Teams Receive 2020 AI Accelerator Awardsen_US
dc.typeArticleen_US


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