What AI Is Teaching Us About Ancient Civilizations

Although teaching people about their old civilizations may seem like a strange task for artificial intelligence, it has potential. Traditionally, archaeological surveys and deciphering are meticulously annoying. This technology can automate or streamline a large part of the process, allowing people at an exponential speed to discover more about the past.

Why AI is needed to teach about old civilizations

Spoken language is more or less universal. Throughout history, the written language has been much rarer. The earliest known writing system is CuneEIFORM, that was invented around 3100 BC. By the Sumerians. Preliterate cut images date up to 4400 BC, so academics have records for thousands of years to flow and translate.

There are also glyphs, earthenware, digging, structures and images, each with a unique story. For centuries, people have carefully identified, deciphered and investigated this curiosities. Launch, discovery and success are worth it – even exciting. However, the progress is slow. Sometimes there is an extremely small number of subject, which causes bottlenecks.

What if researchers didn’t have to wait? What if they could accelerate their progress ten times? With AI that can be possible. An advanced, specially built model could discover secrets that have been hidden for thousands of years.

The power of a machine learning model is in automation and evolution. Because it learns while the new information processes, the evolving as research or archaeological projects are progress, making itself effective future -proof. Moreover, it requires minimal human supervision and can act independently, so that it can carry out complex multistap assignments itself.

What historians have learned about premodern cultures using AI

Although modern AI is relatively new, scientists and archaeologists have already used it to find out more about where premodern people lived and how they communicated.

Words in Langdane Languages

One word can have countless meanings, depending on the intentions of the author and the context of the composition. This complicates decoding. Even simple, meaningless sentences become complex puzzles. The joke “What does a clock do when it is hungry? It goes back for seconds” is a great example because it is a pun. It can be useless in another language.

In the past, computer programs stumbled on these nuances. Natural language processing technology Uses the tagging of the part of the speechTokenization and lemmatization to recognize individual morphemes. With this framework, an algorithm could understand the intricacies of context and meaning, even in long -danded languages.

Usually the manual deciphering of old languages ​​is a difficult, error -sensitive task. Now a model with NLP options in a fraction of the time could decode.

Take, for example, the figurative geoglyph-Pre-Columbian designs that are etched in desert sand-for example. It took almost a century To discover 430 Nazca Geoglyphs Around the Nazca Pampa. With the help of AI, a research team found 303 new, almost the total known number doubled within just six months after the field’s examination.

Where archaeological sites are

Recently a research team of Khalifa University in Abu Dhabi Ai used to identify signs of a 5,000-year-old civilization among the dunes of the Rub al-Khali, the world’s largest desert. Since it extends more than 250,000 square milesIt is notoriously difficult to study. Shifting sand and harsh conditions complicating archaeological surveys.

The research team used satellite images with high resolution and synthetic opening radar technology to detect buried artifacts from space. These results were introduced in a machine learning model for image processing and geospatial analysis, where the research is automated. This approach was accurate within 50 centimetersThe prime of the potential.

Ways in which AI improves the understanding of gone eras

AI also helps scientists to understand more about how old civilizations functioned, giving them a clearer window in the past.

Simulating ancient cultural attitudes

Michael Varnum, the head of social psychology and associate professor at Arizona State University, was recently co-author of an opinion piece proposing to use generative AI to simulate old cultural attitudes.

Existing methods are struggling to discover the mentality or behavior of long -dead cultures. Varnum says people in his field Usually use indirect proxies Such as archive data about crime levels or divorce percentages to divert the values ​​and feelings of people. However, this approach is indirect and inaccurate. His solution is to train an AI to analyze historical texts.

Although AI could derive the opinions and emotions of people from written data, the insights will be skewed. Historically, the ability to read and write was rare. Varmum admits that all insights generated by AI would probably come from well -considered people from the higher class. Since social class influences psychology, the analysis would not result in a fully accurate view of the past.

Reconstructing premodern customs

When archaeologists restore objects from old cemeteries or half -quality cities, the guesswork is involved. Even if they know exactly what something was used for, they may not be able to determine how it works.

In the 1970s, researchers applied a grave at a cemetery of the Bronze Age in Iran. She found the oldest intact board game Once discovered, dating back from 4,500 years. It consisted of 27 geometric pieces, 20 circular spaces and four dice. No Rulebook was buried, so they could only guess how to play.

AI was able to make the rules again and reduce board games for a long time. The Digital Ludeme project does exactly that. It has already spanned three time periods and nine regions, Play almost 1,000 games again. Nowadays these reconstructions are available online for everyone to play.

What else can be learned from these old cultures?

There is much more to learn from AI. CuneEiform is one of the most interesting. Nowadays, academics have access to round 5 million Sumeric wordsMillions more than left Romans in Latin. Many of the many clay tablets discovered in the region still have to be deciphered, and more have been excavated almost daily.

To streamline the process, the AI ​​research team uses to participate in tablet fragments, in which parts are merged to accelerate deciphering. They also train it to decipher cuneiform script, which allows only a handful of experts capable of. The speed of algorithmic processing can make this technology infinitely faster than people.

This new knowledge can fill gaps in history books. Although people have an extensive cultural history, many regions remain unexplored because they have not had the technology. With techniques for machine learning and generative models, they can have a deeper insight into the world and get a new perspective on history.

With the help of AI in uncovering archaeological locations, deciphering long -dead languages ​​and translating old texts, professionals in the industry can find new books, historical reports, artworks and treasures. These findings can be shown in a museum or to help descendants make contact with their ancestors.

The future prospects of AI solutions such as archaeological tools

AI can decipher long -dead languages, find old cemeteries and simulate old practices. The findings could end in history books or museums. Academics must of course step care carefully. Although this technology is powerful, bias, inaccuracies and hallucinations are not uncommon. A human-in-the-loop approach can help them mitigate these problems.