NASA scientists are training computers to search for signs of life on other planets, beginning with Mars. The new intelligent systems, which can identify geochemical signatures of life in rock samples, will be deployed for the first time with the 2022 ExoMars mission.
Victoria Da Poian of the NASA Goddard Space Flight Center (GSFC) presented the exciting research at the Goldschmidt Conference.
“This is a visionary step in space exploration. It means that over time we’ll have moved from the idea that humans are involved with nearly everything in space, to the idea that computers are equipped with intelligent systems, and they are trained to make some decisions and are able to transmit in priority the most interesting or time-critical information,” said Da Poian.
Eric Lyness of the GSFC the Planetary Environments Lab emphasized the need for smart instruments in planetary exploration.
“It costs a lot of time and money to send the data back to Earth which means scientists can’t run as many experiments or analyze as many samples as they would like,” said Lyness. “By using AI to do an initial analysis of the data after it is collected but before it is sent back to Earth, NASA can optimize what we receive, which greatly increases the scientific value of space missions.”
The Mars Organic Molecule Analyzer (MOMA) is a mass spectrometer-based instrument that analyzes and identifies organic molecules in rock samples. The instrument will use these capabilities to search for past or present life on the surface and subsurface of Mars.
Preliminary testing has shown that the system can categorize a spectrum from an unknown compound with up to 94 percent accuracy and match it to samples with 87 percent accuracy, and the instrument is still being refined.
“What we get from these unmanned missions is data, lots of it; and sending data over hundreds of millions of kilometers can be very challenging in different environments and extremely expensive; in other words, bandwidth is limited,” said Da Poian.
“We need to prioritize the volume of data we send back to Earth, but we also need to ensure that in doing that we don’t throw out vital information. This has led us to begin to develop smart algorithms which can for now help the scientists with their analysis of the sample and their decision-making process regarding subsequent operations, and as a longer-term objective, algorithms that will analyze the data itself, will adjust and tune the instruments to run next operations without the ground-in-the-loop, and will transmit home only the most interesting data.”
The system will transmit most of the data back to scientists here on Earth. In the future, these intelligent systems will be used in the outer solar system and will have the intelligence to decide what information to return to Earth.
“When first gathered, the data produced by the MOMA life-searching instrument is difficult to interpret. It will not shout out ‘I’ve found life here,’ but will give us probabilities which will need to be analyzed,” said Lyness.
“These results will largely tell us about the geochemistry that the instruments find. We’re aiming for the system to give scientists directions, for example our system might say ‘I’ve got 91% confidence that this sample corresponds to a real world sample and I’m 87% sure it is phospholipids, similar to a sample tested on July 24th, 2018 and here is what that data looked like.’ We’ll still need humans to interpret the findings, but the first filter will be the AI system.”
The researchers noted that it is very expensive to send data back from Mars. “Data from a rover on Mars can cost as much as 100,000 times as much as data on your cell phone, so we need to make those bits as scientifically valuable as possible.” said Lyness.
The research was presented at the virtual Goldschmidt 2020 conference.