FDL 2019

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FDL 2019 is your chance to be part of something ground-breaking this year.


NASA fdl 2019 challenge areas

The FDL yearly cycle starts with challenge definition. Early in the year, we bring together some of the brightest and best minds we can find, from space science, AI and technology, and on/off-Earth applications to explore our challenge areas. During the course of our day-long Big Think events in Europe and the US, we aim to identify some broad challenges, which the FDL research teams could tackle in the summer.

Through a process of iteration with a PI (principal investigator) leading each challenge, we refine and narrow those challenge areas until we have identified one, or several, tightly articulated questions to resolve.

FDL challenges must represent a clear and present scientific problem, for which there is available data, that could be significantly advanced by AI tools and techniques. It is these challenges that the research teams further narrow in the opening weeks of the FDL research sprint to refine their own particular concept approach. The broad challenge areas we start the year with move from provisional to confirmed as we understand how, and when, they meet these criteria. Our provisional challenge areas for 2019 are:

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Living with Our Star

How can AI improve our ability to predict solar activity - especially energetic solar phenomena?

EXPANDING THE CAPABILITIES OF NASA’S SOLAR DYNAMICS OBSERVATORY

The Solar Dynamics Observatory (SDO) has greatly expanded our understanding of the Sun, but can we use AI to enhance the value of the SDO even more? This will help inform the reduced instrumentation strategy that will be central to the success of future SmallSat missions.

DECIPHERING THE IMPACT OF SOLAR VARIABILITY ON EARTH’S CLIMATE

Weather forecasting has advanced substantially in recent years, but long-term climate trends continues to challenge our understanding of Earth’s environmental dynamics. Can AI help to detect the subtle fingerprints of the solar cycle variability on Earth’s climate?


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The Moon for Good

How might AI support the goal of establishing a permanent presence on the Moon?

LUNAR RESOURCE MAPPING / SUPER RESOLUTION

How might we use data fusion and emerging super-resolution techniques to develop high-resolution lunar resource maps for the coming era of mission planners looking to locate resources for future robotic and human lunar missions.


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Are We Alone?

Can AI help answer the question of whether we are alone in the universe?

SIMULATING LIFE’S GENESIS ENGINE

How might we use the tools of chemical automata coupled with complexity theory and tool sets of fitness landscapes, gradient descent and stochastic hill-climbing to build a simulated engine of “the chemical operating system of life”?

TECHNOSIGNATURE DETECTION

Can we develop an unsupervised method to identify potentially anomalous radio signal data gathered by the SETI Institute’s Allen Telescope Array (ATA)? Useful work could include elimination of human radio frequency interference (RFI) using ML.


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Mission Control for Earth

How might we utilise AI and Earth observation data to support improved decision making to protect the planet?

DISASTER PREVENTION, PROGRESS AND RESPONSE

How can AI improve our capabilities to forecast and respond to natural disasters using orbital imagery, coupled with ground observations and social data?


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Astronaut Health

How can AI support medical care in space?

GENERATION OF SIMULATED BIOSENSOR DATA

NASA deep space missions will require advanced medical capabilities, including continuous monitoring of astronaut vital signs to ensure optimal crew health. Can we use biosensor data collected from NASA analog missions to train AI models to simulate various medical conditions that might affect astronauts?


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Mission Support: Real-Time Data/Virtual Instruments

SMALL-SAT SWARMS AND DISTRIBUTED AI

Can AI help to coordinate the multi-agent actions of a Small Sat swarm to create a “virtual” space platform that is more capable, more flexible, and more resilient than the simple sum of its collective parts? This challenge aims to develop an AI solution that can optimize how SmallSats can collectively take on complex mission goals.

You can read about the FDL Europe 2019 challenges by following this link.