Imagine manually scanning 112,000 photos of Mars for crater formations.

Scientists can estimate the age of old craters on the surface of Mars by looking at the characteristics of new ones that have been captured as images by the Context Camera on NASA’s Mars Reconnaissance Orbiter (MRO). But its tricky to pinpoint which image(s) depict new craters – especially if you have to manually scan the 112K lower-resolution images taken by the MRO over the past 15 years. But an AI algorithm can do the job incredibly faster. (BIG THINK)

Scanning manually, if a scientist finds a new crater in the MRO images, then the discovery is confirmed by referring a higher-resolution photograph taken by the High-Resolution Imaging Science Experiment (HiRISE), another instrument on board the MRO.

How the AI does it

To avoid the laborious and time-consuming manual process, researchers have trained an AI algorithm to analyze the MRO images of Mars’ surface. It takes only five seconds to scan an image and deliver a result.

The researchers fed the algo about 7,000 images taken by the Context Camera and trained to distinguish craters – notably, each image covers hundreds of miles of the surface of Mars.

The researchers then ran the AI and images on a supercomputer cluster at NASA’s Jet Propulsion Laboratory (JPL) with computers processing the task in parallel.

“It wouldn’t be possible to process over 112,000 images in a reasonable amount of time without distributing the work across many computers,” JPL computer scientist Gary Doran said in October. “The strategy is to split the problem into smaller pieces that can be solved in parallel.”

The result: the average time taken by the AI was only 5 seconds per image, compared to about 40 minutes for a scientist scanning manually.

Scientists can now study craters that were formed on Mars as far back as 15 years. These would yield valuable information for estimating the age of much older craters.

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Feature Image: Mars – A Pair of New Impact Craters