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In 2020, Lisa Kaltenegger, an exoplanet astrophysicist and director of the Carl Sagan Institute at Cornell University, and collaborator Dang Pham wondered if machine learning systems could be trained to pinpoint life-enabling resources like water -- something ExoMiner cannot do.
2020年，系外行星天文物理學家、康乃爾大學卡爾薩根研究所所長麗莎·卡爾特內格和合作者范滕想知道是否可以訓練機器學習系統來精確定位水等孕育生命的資源，這是Exo Miner無法做到的。
"If you find ice, you can infer water," Kaltenegger says. "If you can find clouds, you infer water. So we asked, how good is it in finding water, clouds, and ice?"
“如果你找到冰，你就可以推斷出水，”卡爾特內格說。“如果你能找到云，你就能推斷出水。所以我們發問，尋找水、云和冰有多好？
Kaltenegger and Pham used measurements of the Earth's atmosphere to simulate exoplanets with a rocky surface, water, clouds, and ice.
卡爾特內格和范滕利用地球大氣層的測量來模擬具有巖石表面、水、云和冰的系外行星。
They also trained an algorithm to look for a sign of life called a red edge, wavelengths of light that plants reflect back into space.
他們還訓練了一種算法來尋找生命跡象，稱為紅邊，即植物反射回太空的光波長。
They found their software could detect the existence of life in a simulated atmosphere about three-quarters of the time, which could greatly improve the initial hunt for another Earth.
他們發現他們的軟件可以在大約四分之三的時間內檢測到模擬大氣中生命的存在，這可以極大地改善對另一個地球的最初搜尋。
"I thought it would be very, very hard to do, but machine learning algorithms are quite effective in finding patterns in the data," Kaltenegger says.
“我認為這非常非常難做到，但機器學習算法在尋找資料模式方面非常有效，”卡爾特內格說。
The computer programs were best at spotting the telltale signs of leafy plants and less reliable when looking for evidence of lichen, tree bark, or biofilm.
電腦程序最擅長發現綠葉植物的跡象，但在尋找地衣、樹皮或生物膜的證據時不太可靠。
There are caveats. These algorithms cannot provide absolute certainty. Rather, one could estimate that some percentage of a planet's surface is covered with life.
有一些警告。這些算法不能提供絕對的確定性。相反，人們可以估算出行星表面的一定比例被生命覆蓋。
That's not the same as a discovery, Kaltenegger points out. Instead, it's a helpful clue.
卡爾特內格指出，這與發現不同。相反，這是一個有用的線索。
"It's not going to be like, AI said we found an Earthlike planet," she explains. "AI is going to bring it to the level where some real people are going to have to look at it."
“人工智能不會說我們發現了一顆類地行星，”她解釋道。“人工智能將把它提升到一些真實的人必須審視它的水平。”
Human scientists will still need to point more telescopes toward the planet and look for chemical signatures that could indicate life is there.
人類科學家仍然需要將更多的望遠鏡指向這顆行星，尋找可能顯示生命存在的化學特征。
Ultimately, real people will be the ones deciding what such a discovery means.
最終，真實的人將決定這項發現的意義。
