Teaching humans about ancient civilizations may seem like a strange job for artificial intelligence, but that can be the case. Traditionally, archaeological research and deciphering has been painfully boring. This technology can automate or streamline most of the process, helping people to reveal more about the past at an exponential speed.
Why AI is needed to teach about ancient civilizations
Spoken language is more or less universal. Throughout history, written languages are much rarer. The earliest known lighting system is mucus It was invented around 3100 BC. By the Sumerians. The engraved images date back to 4400 BC, so scholars have thousands of years of records that they translate and translate.
There are also glyphs, pottery, graves, structures and statues, each with a unique story. For centuries, humans have been struggling to identify, decipher and investigate these curiosities. Pursuing, discovering, and success is rewarding – and even thrilling. However, progress is slow. Sometimes there are very few subjects that create bottlenecks.
What happens if the researcher has to wait? What if you could accelerate your progress by 10 times? With AI, that might be possible. Advanced, dedicated models can reveal secrets that have been hidden for thousands of years.
The power of machine learning models lies in automation and evolution. Learning as new information is processed, and as research and archaeological projects progress, effectively potentially future prevention itself. Additionally, it requires minimal human surveillance, allowing it to act independently, and perform complex multi-step assignments on its own.
What historians learned about premodern culture using AI
Modern AI is relatively new, but scientists and archaeologists have already used it to learn more about where pre-modern people live and how they communicated.
Long-standing language language
A word can have countless meanings depending on the author’s intention and context of composition. This complicates deciphering. Even simple, meaningless phrases become complicated puzzles. The joke “What does the clock do when you’re hungry? It’s back for a few seconds” is a great example because it’s a play on words. In another language, that may make no sense.
In the past, computer programs have stumbled over these nuances. Natural Language Processing Technology Use some speech taggingtokenization and lemmatization for recognizing individual morphemes. Using this framework, algorithms can grasp the complexity of context and meaning, even in long term languages.
Manually deciphering ancient languages was usually a tedious and error-prone task. Now, models with NLP functionality can decode languages written in a fraction of the time.
Take, for example, a pre-Columbus design etched into desert sands – a urological geoglyph – a pre-Columbus design. It took almost a century Discover 430 Nazca Geoglyphs Around Nazca Pampa. Using AI, the research team discovered 303 new teams, nearly doubled the known total within just six months of the field survey.
Places with archaeological locations
Recently, researchers from Khalifa University in Abu Dhabi used AI to identify signs of a civilization that was 5,000 years ago under the dunes of Rub Al-Khali, the world’s largest desert. after that It will extend over 250,000 square milesIt is known for its difficult study. Changing sand and harsh conditions complicates archaeological investigations.
The researchers used high-resolution satellite imagery and synthetic aperture radar technology to detect buried artifacts from space. These results were fed into machine learning models for image processing and geospatial analysis to automate the investigation. This approach It was accurate within 50cmindicating the possibility.
How AI is improving our understanding of the past era
AI is also helping scientists understand more about how ancient civilizations work, giving them a clear window into the past.
Simulate ancient cultural attitudes
Michael Varnum, principal and associate professor of the Social Psychology Area at Arizona State University, recently co-authored an opinion that he proposed using generated AI to simulate ancient cultural attitudes.
Existing methods struggle to clarify cultural thinking and behavior over the years. Varnum says people in his field Usually, you use an indirect proxy It infers people’s values and feelings, as well as archival data on crime levels and divorce rates. However, this approach is indirect and inaccurate. His solution is to train AI to analyze historical texts.
However, AI can infer people’s opinions and feelings from written records, but their insights are distorted. Historically, literacy has been rare. Varmum acknowledges that insights generated in AI are likely to come from educated, upper class individuals. Because social class influences psychology, analysis does not provide a complete, accurate glimpse into the past.
Reconstruction of pre-modern customs
Assumptions are involved whenever archaeologists retrieve objects from ancient burial sites or half-hearted cities. Even if they know exactly what something was used, they may not be able to determine how it works.
In the 1970s, researchers unearthed graves in Iran’s Bronze Age cemetery. They are Found the oldest unharmed board game It has been discovered so far and dates back 4,500 years. It consisted of 27 geometric parts, 20 circular spaces, and four dice. The rulebook was not filled, so they could only guess how they would play.
AI was able to recreate the rules and regain a long-forgotten board game. The Digital Ludeme Project does just that. Already, it spans three periods and nine regions, Makes you play almost 1,000 games Also. Today, these reconfigurations are available online for anyone to play.
What more can we learn from these ancient cultures?
There is still much more left to learn from AI. Cuneiform is one of the most interesting. Today, scholars can access the area 5 million Sumerian languagesmillions more than the Romans left in Latin. Many of the numerous clay tablets discovered in the area have not yet been deciphered and are excavated almost daily.
To streamline the process, the researchers use AI to combine tablet fragments and stitch together parts to accelerate deciphering. They are also training it to decipher Cuneiform. Due to the speed of algorithm processing, this technology can be infinitely faster than humans.
This new knowledge can fill the gaps in history books. Humans have a vast cultural history, but many regions remain unexplored because they do not have the technology. Machine learning technology and generative models allow them to gain a deeper understanding of the world and gain a new perspective on history.
With the help of AI in discovering archaeological sites, deciphering languages over time, and translating ancient texts, industry experts were able to find new books, historical accounts, works, and treasures. These findings can be displayed in museums and can help descendants connect with their ancestors.
Future outlook for AI solutions as an archaeological tool
AI can decipher long term languages, find ancient burial sites, and simulate ancient practices. The findings could end up in history books and museums. Of course, scholars should take a cautious step. Although this technique is powerful, bias, inaccuracy and hallucination are not uncommon. The human approach to loop helps to alleviate these problems.
