While teaching ancient civilization to humans seems like a strange job for artificial intelligence, it has potential. Traditionally, archaeological investigations and decryption are very cumbersome. This technology can automate or simplify most of the process, helping people reveal more about the past at an exponential rate.
Why AI is needed to teach ancient civilizations
Spoken language is more or less common. Written language has been scarce throughout history. The earliest known writing system is cuneiform. It was invented around 3100 BC. By Sumerians. The pre-carved images date back to 4400 BC, so scholars have thousands of years of records that can be poured into and translated.
There are also glyphs, pottery, graves, structures and statues, each with a unique story. For centuries, humans have been arduously identifying, deciphering and studying these antiques. Pursuit, discovery, and success make sense and even exciting. However, the progress is slow. Sometimes, there are a lot of themes that form bottlenecks.
What if the researchers don’t have to wait? What if they can speed up their progress tenfold? Using AI, this may be possible. A high-end, specially built model could reveal secrets hidden for thousands of years.
The power of machine learning models lies in automation and evolution. Because it learns while processing new information, it can develop as research or archaeological projects progress, effectively preventing the future. Furthermore, it requires minimal human supervision and can act independently, allowing it to perform complex multi-step tasks on its own.
Historians learn about premodern culture using artificial intelligence
Although modern AI is relatively new, scientists and archaeologists have used it to learn more about the residences of pre-modern people and how they communicate.
Words of long-lasting language
A word can have countless meanings, depending on the author’s intention and the context of the composition. This complicates decryption. Even simple, meaningless phrases can become complex problems. The joke “Clock is hungry? It’s going back for a few seconds” is a great example because it’s a drama on the word. In different languages, it may be meaningless.
In the past, computer programs stumbled upon these nuances. Natural language processing technology Use speech section marksymbolize and bait to identify individual morphemes. Using this framework, algorithms can grasp the complexity of context and meaning even in long-term languages.
Often, manually decrypting ancient languages is a laborious and error-prone task. Now, models with NLP capabilities can decode written languages in a very short time.
Take symbolic geographic elements as an example – For example, the former Colombian design was engraved in desert beaches. It took nearly a century 430 NASCAR geographic elements were found Near Naska Bangpa. A research team used AI to discover 303 new teams, and the total was nearly doubled within just six months after field measurements.
Where is the archaeological site
Recently, a team from Khalifa University in Abu Dhabi used artificial intelligence to identify signs of 5,000 years of civilization under the sand dunes of Rub al-Khali, the world’s largest desert. Since then Extended over 250,000 square milesas we all know, it is difficult to learn. The transfer of sand and harsh conditions complicates archaeological investigations.
The team used high-resolution satellite imagery and synthetic aperture radar technology to detect artifacts buried in space. These results are fed into machine learning models for image processing and geospatial analysis, thereby automating the research. This method Accurate within 50 cmprove its potential.
AI is improving understanding of past times
AI can also help scientists understand more about how ancient civilizations work, thus allowing them to enter the past more clearly.
Simulate ancient cultural attitudes
Michael Varnum, an associate professor in the field of social psychology and associate professor at Arizona State University, recently co-wrote an opinion article suggesting the use of generative AI to simulate ancient cultural attitudes.
Existing methods are difficult to reveal long-term cultural mentality or behavior. Varnum says his person Indirect proxy is usually used For example, archival data on crime levels or divorce rates to infer people’s values and feelings. However, this approach is indirect and inaccurate. His solution is to train AI to analyze historical texts.
But while AI can infer people’s opinions and emotions from written records, its insights tend to be biased. Historically, there was very little literacy. Varmum acknowledges that any AI-generated insights can come from educated upper class people. Since social class affects psychology, this analysis does not fully understand the past.
Reconstruct pre-modern customs
Whenever archaeologists recover objects from ancient funerals or semi-buried cities, guesswork is involved. Even if they know exactly what they are using, they may not be able to determine how it works.
In the 1970s, researchers excavated a grave in the Bronze Age cemetery in Iran. them Found the oldest complete board game It was once discovered, dating back to 4,500 years. It consists of 27 geometric fragments, 20 circular spaces and 4 dices. There is no rulebook buried, so they can only guess how to play.
AI can re-brand rules to bring back long-standing board games. That’s what the Digital Ludeme project does. It has spanned three periods and nine regions, Make nearly 1,000 games playable again. These rebuilds are available online for anyone to play today.
What else can you learn from these ancient cultures?
There is more to learn from AI. Cuneiform is one of the most interesting ones. Today, scholars can enter the surroundings 5 million Soviet-American wordsMore than the millions left in Latin by the Romans. Many of the many clay flakes found in the area have not been declassified and are unearthed almost every day.
To simplify the process, the research team used AI to add tablet fragments and pieced together parts to speed up decryption. They are also training it to decipher cuneiform, which only a few experts have the ability. The speed of algorithm processing can make this technology faster than humans.
These new knowledge can fill gaps in history books. Even though humans have a vast cultural history, many areas are still not explored because they do not have this technology. With machine learning techniques and generative models, they can gain a deeper understanding of the world and thus gain new perspectives in history.
With the help of AI, industry professionals can find new books, history records, artworks and treasures that reveal archaeological sites, decrypt long-term languages and translate ancient texts. These findings can be displayed in museums and can also help future generations connect with their ancestors.
Future Prospects of AI Solutions as Archaeological Tools
Artificial intelligence can decipher long-term languages, find ancient cemeteries and simulate ancient customs. Its discovery may end up in history books or museums. Of course, scholars should act with caution. Although this technology is powerful, bias, inaccuracy and hallucination are not uncommon. Human methods can help them alleviate these problems.
