AI News, Mysterious 15th century manuscript decoded by computer scientists using artificial intelligence

Mysterious 15th century manuscript decoded by computer scientists using artificial intelligence

Artificial intelligence has allowed scientists to make significant progress in cracking a mysterious ancient text, the meaning of which has eluded scholars for centuries.

By applying algorithms designed to decode such puzzles, Professor Kondrak and his graduate student Bradley Hauer were able to decipher a relatively high number of words using Hebrew as their reference language.

However, following tweaks to the spelling, the scientists used Google Translate to convert it into English, which read: “She made recommendations to the priest, man of the house and me and people.” “It’s a kind of strange sentence to start a manuscript but it definitely makes sense,” said Professor Kondrak.

While fully comprehending the text will require collaboration with historians of ancient Hebrew, Professor Kondrak has great faith in the ability of computers to help understand human language and said he is looking forward to applying his techniques to other ancient scripts.

Mysterious 15th century manuscript decoded by computer scientists using artificial intelligence

Artificial intelligence has allowed scientists to make significant progress in cracking a mysterious ancient text, the meaning of which has eluded scholars for centuries.

Taking the first line as an example, Professor Koppel confirmed that it was not a coherent sentence in Hebrew.  However, following tweaks to the spelling, the scientists used Google Translate to convert it into English, which read: “She made recommendations to the priest, man of the house and me and people.” “It’s a kind of strange sentence to start a manuscript but it definitely makes sense,” said Professor Kondrak.

In their paper, the researchers conclude that the text in the Voynich manuscript is likely Hebrew with the letters rearranged to follow a fixed order.  While fully comprehending the text will require collaboration with historians of ancient Hebrew, Professor Kondrak has great faith in the ability of computers to help understand human language and said he is looking forward to applying his techniques to other ancient scripts.

Using AI to uncover the mystery of Voynich manuscript

The mysterious text in the 15th-century Voynich manuscript has plagued historians and cryptographers since its discovery in the 19th century.

Recently, U of A computing science professor Greg Kondrak, an expert in natural language processing, and graduate student Bradley Hauer used artificial intelligence to decode the ambiguities in human language using the Voynich manuscript as a case study.

Their first step was to address the language of origin, which is enciphered on hundreds of delicate vellum pages with accompanying illustrations.

They initially hypothesized that the Voynich manuscript was written in Arabic but after running their algorithms, it turned out that the most likely language was Hebrew.

Kondrak and Hauer hypothesized the manuscript was created using alphagrams, defining one phrase with another, exemplary of the ambiguities in human language.

'It turned out that over 80 per cent of the words were in a Hebrew dictionary, but we didn't know if they made sense together,' said Kondrak.

''She made recommendations to the priest, man of the house and me and people.' It's a kind of strange sentence to start a manuscript but it definitely makes sense.'

An avid language aficionado, Kondrak is renowned for his work with natural language processing, a subset of artificial intelligence defined as helping computers understand human language.

Using AI to uncover ancient mysteries

Computing scientists at the University of Alberta are using artificial intelligence to decipher ancient manuscripts.

This ancient mystery made its way to the artificial intelligence community, where computing science professor Greg Kondrak was keen to lend his expertise in natural language processing to the search.

Kondrak and his graduate student Bradley Hauer set out to use computers for decoding the ambiguities in human language using the Voynich manuscript as a case study.

The next step is how do we decipher it.” Kondrak and Hauer hypothesized the manuscript was created using alphagrams, defining one phrase with another, exemplary of the ambiguities in human language.

It’s a kind of strange sentence to start a manuscript but it definitely makes sense.” Without historians of ancient Hebrew, Kondrak explained that the full meaning of the Voynich manuscript will remain a mystery.

An avid language aficionado, Kondrak is renowned for his work with natural language processing, a subset of artificial intelligence defined as helping computers understand human language.

AI didn’t decode the cryptic Voynich manuscript — it just added to the mystery

If you were compiling a list of the world’s 100 oddest objects — just the weirdest stuff that human civilization has excreted over the millennia — then you’d have to leave room somewhere for the Voynich manuscript.

In it, computer science professor Greg Kondrak and graduate student Bradley Hauer describe a method for finding the source language of ciphered texts, before turning that method on the manuscript itself, and deciding that it was originally written in Hebrew, before being encoded in its current form.

Scattered throughout are illustrations of unidentifiable plants, astrological diagrams, doodles of castles and dragons, and a particularly odd section that shows naked women bathing in pools connected by flowing tubes.

“I’ve seen suggestions that it’s encoding Arabic, Aztec, Roma, Latin, Italian.” Davis says people tend to study the “paleographic, forensic, and artistic evidence” to find a country of origin, and with that, a source language, but she adds that computational analysis is also used.

They figured, like many cryptologists before them, that by computing certain qualities of the text — like, for example, how often each letter and each combination of letters appear — they could create a statistical fingerprint that could be compared to other languages.

(Despite what some coverage suggested, this process did not involve neural networks or deep learning — just good old-fashioned statistical analysis, aka lots of counting and percentages.) And it worked!

According to Professor Shlomo Argamon, a computational linguist at Illinois Institute of Technology, the preliminary test results are “perhaps slightly questionable, but not more so than many other results often published in the scientific literature.” And so, with their algorithmic pattern-matcher trained and tested, Kondrak and Hauer turned to the Voynich manuscript.

The sentence in question is this: “She made recommendations to the priest, man of the house and me and people.” Kondrak says, “It’s a kind of strange sentence to start a manuscript but it definitely makes sense.” But even within the paper, he and Hauer describe how they had to fudge the translation to produce this result.

(“Any time you have to resort to Google Translate over someone who has actually studied the language, you’re going to lose some credibility,” notes Fagin.) But this is where the assumption that the manuscript was written in anagrams becomes even more crucial.

If you assume that the manuscript was written in Hebrew and that it’s written in anagrams, then it becomes much, much easier to “translate.” Then, not only can you rearrange all the characters in a word to find something that makes sense, but you can add in your own vowels.

As Pelling said in a final email: “Through my book [...] and my blog, I’ve probably written more actual historical research about the Voynich than anyone else alive: I’ve given talks on it, and made a TV documentary on it, and have been interviewed about it on radio and TV numerous times… And I still can’t read it.

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