Lexical borrowing is very widespread and may affect even those words that play an important role in our daily life. English'mountain', for example, was borrowed from Old French, along with many other words. Researchers from the Pontificia Universidad Católica del Perú and the Max Planck Institute for the Science of Human History have investigated the ability of machine learning algorithms to identify lexical borrowings using word lists from a single language. Results published in the journal PLOS ONE show that current machine-learning methods alone are insufficient for borrowing detection, confirming that additional data and expert knowledge are needed to tackle one of historical linguistics' most pressing challenges. Lexical borrowing, or the direct transfer of words from one language to another, has interested scholars for millennia, as evidenced in Plato's Kratylos dialog, in which Socrates discusses the challenge imposed by borrowed words on etymological studies.
Artificial intelligence offers a chance for the Latin America's economies to leapfrog to greater innovation and economic progress. E-commerce firms have faced a conundrum in Latin America: How can they deliver packages in a region where 25% of urban populations live in informal, squatter neighborhoods with no addresses? Enter Chazki, a logistics startup from Peru, which partnered with Arequipa's Universidad San Pablo to build an artificial intelligence robot to generate new postal maps across the country. The company has now expanded to Argentina, Mexico and Chile, introducing remote communities and city outskirts to online deliveries. That's just one example of how machine learning is bringing unique Latin American solutions to unique Latin American challenges.
So far it is not precisely known, how much water a continent really stores. The continental water masses are also constantly changing, thus affecting the Earth's rotation and acting as a link in the water cycle between atmosphere and ocean. Amazon tributaries in Peru, for example, carry huge amounts of water in some years, but only a fraction of it in others. In addition to the water masses of rivers and other bodies of fresh water, considerable amounts of water are also found in soil, snow and underground reservoirs, which are difficult to quantify directly. Now the research team around primary author Christopher Irrgang developed a new method in order to draw conclusions on the stored water quantities of the South American continent from the coarsely-resolved satellite data.
Trapezoids, triangles and many other geometric shapes -- that's what one would see if they flew a drone over the high desert in Peru, South America. These giant geometric figures resemble birds, insects and other living beings. These are the famous Nazca lines which were discovered in the 1920s. In total, there are over 800 straight lines and 300 geometric figures. Archaeologists have been studying these lies ever since their discovery and still continue to do so till date.
Ever heard of the Nasca Lines? They're literal lines etched in the sands of southern Peru covering an area of nearly 1,000 square kilometers, which depict over 300 different figures including animals and plants. The best evidence suggests that they're pre-Columbian in origin, dating from between roughly 500 BC and 500 AD, and that they might mark solstice points or serve as offerings to ancient deities. Although the Nasca Lines have been studied for decades (and more intensely since they were designated a UNESCO World Heritage site in 1994), they've yet to be fully mapped. Yamagata used IBM's Watson Machine Learning Accelerator (WMLA) -- a framework designed to handle large-scale workloads spanning clusters of machines -- to expedite their analyses.
IBM power systems and Yamagata University collaborated to develop an AI-enabled cloud platform and geoscope that uncovered mysterious and ancient geoglyphs. Could robots become archaeological assistants, shuffling or trudging across sandy terrain like R2D2 and C3P0 in 1977's original " Star Wars?" Artificial Intelligence (AI) and machine-learning algorithms, along with geospatial data, are being used to uncover mysterious and ancient geoglyphs, courtesy of a collaboration between IBM power systems and Yamagata University. And, using the new AI, scientists discovered a new formation of very large geoglyphs in the soil on the Nazca Lines in southern Peru-- the first to be found using AI. While straight lines dominate the Nazca desert landscape, figurative designs of animals and plants have evolved.
Located in the Nazca Desert in southern Peru, the Nazca Lines are a collection of giant etchings that only make sense from a great height. Now AI is helping speed up the hunt for more hidden symbols--and has already had some success. Mysterious sand symbols: Since their discovery in the 1920s, the Nazca Lines have continued to mystify experts. Created between 200 BCE and 600 CE, they were made by removing stones to reveal the white sand beneath and depict various geometric shapes, people, and animals, known as geoglyphs. In 1994 they were designated a UNESCO World Heritage Site, but their purpose and meaning have continued to elude historians.
Artificial intelligence has helped archaeologists uncover an ancient lost work of art. The Nazca Lines in Peru are ancient geoglyphs, images carved into the landscape. First formally studied in 1926, they depict people, animals, plants, and geometric shapes. The formations vary in size, with some of the biggest running up to 30 miles long. Their exact purpose is unknown, although some archaeologists think they may have had religious or spiritual significance.
YAMAGATA – Yamagata University has announced the discovery of 143 geoglyphs on the Nazca Pampa and surrounding areas in Peru, including one found in a study using artificial intelligence technology. The university's team, led by professor Masato Sakai, found 142 geoglyphs, including ones depicting humans, snakes and birds, through analysis of high-resolution images of the areas and fieldwork there between 2016 and 2018. The research was based on a hypothesis that many geoglyphs were created along small paths in the western region of the Nazca Pampa, according to the university's announcement Friday. The team conducted the AI-based study with cooperation from IBM Japan Ltd. between 2018 and 2019. The world's first such study analyzed aerial photographs using deep-learning techniques to look for what are likely to be geoglyphs.