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Google AI researcher Pietro Miotti let his AI agents loose on some NASA lidar data \u2014 where, according to him, they made a staggering discovery: an ancient Maya site lurking deep under the thick canopy of the jungles of Mexico.<\/p>\n
\u201cBy analyzing NASA lidar data, my AI agents discovered a Maya site in Mexico that, as far as anyone can tell, no one had reported before,\u201d Miotti wrote in a breathless blog post<\/a>. \u201cIt took less than 72 hours to go from a random thought while traveling to an official reply from the Mexican government.\u201d<\/p>\n \u201cThis is by far the best time ever to be alive,\u201d the researcher, who admitted that he\u2019s \u201cnot an archeologist,\u201d gushed.<\/p>\n \u201cI think we\u2019re on the brink of a revolution across every science, not just coding, physics and math,\u201d he tweeted<\/a>.<\/p>\n The discovery blew up on social media, with users lauding him<\/a> for \u201cfinding ancient mayan sites from your desk chair\u201d and arguing that the discovery justified AI data centers<\/a>. (Naturally, they also shared AI slop images<\/a> of what the site could look like once unearthed.)<\/p>\n The news even caught the attention of media outlets, including The Verge<\/a> and TechRadar<\/a>.<\/p>\n But it didn\u2019t take long for the scientific community to call foul. <\/p>\n \u201cThis story is going wild on X and elsewhere,\u201d archeologist and award-winning author Sarah Parcak wrote in a post on Bluesky<\/a>. \u201cThe site was already published by Dr. Francisco Estrada-Belli of Tulane University ages ago.\u201d<\/p>\n In a 2025 paper<\/a>, a team of researchers directed by Estrada-Belli examined lidar data colleceted by NASA\u2019s Goddard Space Flight Center, covering 95,000 square kilometers of central America, finding that the ancient Maya population may have been significantly larger than previously estimated, possibly upwards of 16 million people<\/a> at its peak.<\/p>\n \u201cThis is why we have peer review,\u201d Parcak added. \u201cMexican gov didn\u2019t have it in their database, but that doesn\u2019t mean it is unknown\/unmapped.\u201d<\/p>\n Estrada-Belli shared images of the site<\/a> with Parcak, adding credence to the revelation.<\/p>\n To his credit, Miotti admitted defeat, conceding in an update that \u201cit turns out the site had already been mapped.\u201d<\/p>\n \u201cThe agents missed it while going through the literature, so they rediscovered it rather than discovered it,\u201d Miotti claimed. \u201cStill work to do then!\u201d<\/p>\n Nonetheless, the incident highlights a trend of AI researchers being accused of taking credit for pre-existing scientific research. Perhaps the most notable is OpenAI, which released a flood of \u201cproofs\u201d for well-known, unsolved mathematical problems. But many of these solutions appear to be ripping off the work of mathematicians<\/a>, who were actively working on the puzzles.<\/p>\n The incident escalated into a crisis<\/a> earlier this year as mathematicians accused OpenAI of providing unverified proofs and relying on plagiarism. It underscored how the entire AI industry has built its foundations by effectively ripping off rights-protected content on the web and using it to train their models.<\/p>\n While Miotti thankfully admitted that his AI agents had discovered a site that we already knew about for years, that doesn\u2019t mean other researchers will make similar claims that may go by undisputed and taken for granted.<\/p>\n Besides, ironically, machine learning and computer vision have long been a \u201ccore part of remote sensing for as long as it\u2019s been around,\u201d geoscience consultant Alex Janevski wrote in a post on Bluesky<\/a>.<\/p>\n \u201cI hate how this sort of hyperbolic misinformation both takes credit away from the actual experts and distorts how those experts are of course already using advanced digital tools of various kinds and have been for decades,\u201d Roman historian Anise Strong wrote<\/a>. \u201cDon\u2019t reinvent the wheel, Random Internet Guy!\u201d<\/p>\n