
AI Revolutionizes Archaeology, Biology, and Communication in 2024 | Image Source: www.cnn.com
ATLANTA, December 21, 2024 – Artificial Intelligence (AI) ​has emerged as a ​transformative tool in various scientific disciplines, significantly advancing understanding in archaeology, biology and animal communication. From the decoding ​of ancient Roman rolls to the mapping of unexplored geoglyphs in the Nazca desert, AI applications reshape ​scientific discovery. According to CNN, these advances illustrate how machine learning can amplify human knowledge ​to solve ancient mysteries and make unprecedented discoveries.
Decoding old plums
One of the most striking manifestations of AI’s potential is the current Vesuvius Challenge, which seeks to unlock the ​secrets of ​the Herculaneum rolls. The carbonized papyrus, buried by the eruption of Mount Vesuvius in 79 AD, contain ​invaluable ideas about ancient Rome and Greece. The researchers used high ​resolution X-rays and AI tools to decode more than 2,000 characters, revealing Greek text texts without physically unlocking fragile movements. Brent Seales, professor of computer science at the University of ​Kentucky, explained that AI condemns and amplifies the few ink ​tests hidden in the carbonized material. He said, “IA helps us to amplify the ​readability of ink evidence.”
According to the Vesuvius Challenge team, its goal is to decode 90% of the text of four rolls by ​the ​end ​of 2024. This achievement highlights the role ​of AI as ​a “superpower”, allowing scientists to analyze data beyond human visual capabilities. In a broader context, ​the ​development of ​AI ​was recognized this year when the Nobel Committee ​awarded the Physical Award to John Hopfield and Geoffrey ​Hinton for their pioneering work in machine learning.
Unveiling models ​in communication with whales
AI ​not only ​unlocks human history, but also decodes the enigmatic ​clicks of sperm, an incomprehensible form of communication to humans. Researchers used machine ​learning to ​analyze nearly 9,000 recorded sequences, called codes, 60 whales in the Caribbean. ​These sequences vary in rhythm, tempo and ornamentation, involving complex language. Although machine ​learning has identified ​models that ​have not yet been observed, the true ​meaning of these vocalizations remains difficult. Interactive ​experiences and behavioral observations are the next steps to unravel the syntax of these sounds, ​as ​noted ​by Brenda McCowan of the University of California, Davis.
The results may one day ​allow humans to communicate with marine ​animals and may be applied to other species. However, AI’s ability to detect models does not extend to interpreting its ​semantic significance. The approach provides a basis for further exploration, ​combining AI and traditional observation methods.
Cartography of hidden geoglyphs in Peru
AI also revolutionizes archaeology. In the Nazca Desert in Peru, ​researchers led by Masato Sakai of the University of Yamagata used AI ​to identify ​over 1,300 previously unknown geoglyphs. These figures, from ​geometric models to animal symbols, were ​previously undetectable without aerial surveys. A high-resolution ​CEW model allowed the ​team to quickly study vast desert areas, thereby reducing potential ​sites for ​physical exploration.
Despite its success, the AI model generated many false positives, identifying 47,000 potential sites, of which only a fraction was significant. However, the speed and magnitude of AI-assisted analysis have ​far exceeded traditional methods, making it an indispensable tool for ​archaeologists working in remote and difficult environments. As ​Amina Jambajantsan of the Max Planck Institute ​pointed out, collaboration between ​data scientists and archaeologists remains essential to the development of these technologies.
Progress in predicting protein structure
AI has also made innovative contributions to biology. DeepMind Alpha The Fold tool, developed by Demis Hassalis and John Jumper, ​predicted the structures of almost all known ​proteins, a milestone in understanding the ​building blocks of ​life. This has accelerated research in areas ranging from molecular biology to ​medicine. According to the Royal Swedish ​Academy of Sciences, which awarded Hassalis and Jumper the Nobel ​Prize in Chemistry of 2024, AlphaFold represents ​”great progress” in protein ​research.
While Alfa Pold has revolutionized the prediction of protein structure, it has ​limits. ​For example, it ​seeks to predict the effects of mutations on protein structures, a critical aspect of disease research. ​Despite these challenges, AI tools such as AlphaFold have made ​important discoveries, including new antibiotics to fight drug-resistant bacteria and advances in cell ​mapping.
The broader implications of AI in science
The integration of AI into scientific ​research is not without concern. The Royal ​Society of the United ​Kingdom cautioned against the “black” character of many ​AI models, which may limit ​the reproducibility of the results. In addition, bias in AI training data poses ethical risks, particularly in applications such as ​recruitment and police. However, the benefits of IA in science are obvious, the nature of which indicates that more than half of the scientists interviewed consider IA tools essential to their work.
From the decryption ​of ancient texts to the disengagement of the mysteries of life and communication, AI continues to push the limits of ​what humanity can achieve. As Brent Seales summed up, “IA is a computer field designed to try to ​solve problems in a way that we think only humans could solve problems”
Through ​its growing influence across disciplines, AI is able to redefine how discoveries are made, fill gaps ​in knowledge, and open new boundaries for exploration.