AI Weekly: In a chaotic year, AI is quietly accelerating the pace of space exploration

The year 2020 continues to be difficult here on Earth, where the pandemic is exploding again in regions of the world that were once successful in containing it. Germany reported a record number of cases this week alongside Poland and the Czech Republic, as the U.S. counted 500,000 new cases. It’s the backdrop to a tumultuous U.S. election, which experts fear will turn violent on election day. Meanwhile, Western and Southern states like Oregon, Washington, California, and Louisiana are reeling from historically destructive wildfires, severe droughts, and hurricanes.

Things are calmer in outer space, where scientists are applying AI to make exciting new finds. Processes that would’ve taken hours each day if performed by humans have been reduced to minutes, a testament to the good AI can achieve when used in a thoughtful way. While not necessarily groundbreaking, unprecedented, or state-of-the-art with regard to technique, the innovations are inspiring stories of discovery at a time when there isn’t a surfeit of hope.

Earlier this month, researchers at NASA’s Jet Propulsion Laboratory in California announced they’d fed an algorithm 6,830 images taken by the Context Camera on NASA’s Mars Reconnaissance Orbiter (MRO) to identify changes to the Martian surface. Given 112,000 images taken by the Context Camera, the AI tool spotted a cluster of craters in the Noctis Fossae region of Mars, including 20 new areas of interest that might have formed from a meteor impact between March 2010 and May 2012. NASA hopes to use similar classification technology on future Mars orbiters, which might provide a more complete picture of how often meteors strike Mars.

In August, researchers at the University of Warwick built a separate AI algorithm to dig through NASA data containing thousands of potential planet candidates. The team trained the system on data collected by NASA’s now-retired Kepler Space Telescope, which spent nine years in deep space searching for new worlds. Once it learned to separate planets from false positives, it was used to analyze datasets that hadn’t yet been validated, which is when it found 50 exoplanets.

And last week, Intel, the European Space Agency (ESA), and startup Ubotica detailed what they claim is the first AI-powered satellite to orbit Earth: the desktop-sized PhiSat-1. It aims to solve the problem of clouds obscuring satellite photos by collecting a large number of images from space in the visible, near-infrared, and thermal-infrared parts of the electromagnetic spectrum and then filtering out cloud-covered images using AI algorithms. Future versions of the PhiSat-1 could look for fires when flying over areas prone to wildfire and notify responders in minutes rather than hours. Over oceans, which are typically ignored, they might spot rogue ships or environmental accidents, and over ice, they could track thickness and melting ponds to help monitor climate change.

AI is problematic in many respects; it’s biased, discriminatory, and harmful at its worst. We’ve written about how facial recognition algorithms tend to be less accurate when applied to certain racial and ethnic groups. Natural language processing models embed implicit and explicit gender biases, as well as toxic theories and conspiracies. And governments are investigating the use of AI and machine learning to wage deadly warfare.

This being the case, some AI — like that applied to Martian landscapes, telescope snapshots, and cloudy satellite images — can be a force for good. And in a year marked by tragedy and general skepticism about technology (and the tech industry), this positivity isn’t just encouraging, but sorely needed.

For AI coverage, send news tips to Khari Johnson and Kyle Wiggers — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI channel, The Machine.

Thanks for reading,

Kyle Wiggers

AI Staff Writer

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