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Posts Tagged ‘ancient text’

Images: Public domain.
Depictions of sea creatures in 13th C manuscripts
. How marvelous these illustrations are!

The maritime archaeologist in today’s article says it was just a coincidence that he was reading ancient Norse texts and connected the description of a sea creature to recent observations of whales. But I believe it’s not a coincidence. Everything connects to everything, and the more widely you read, the more likely you are to find the connections.

The researchers noted: ‘Definitive proof for the origins of myths is exceedingly rare and often impossible, but the parallels here are far more striking and persistent than any previous suggestions.’

Donna Lu writes at the Guardian, “Mysterious whale feeding behavior only documented by scientists in the 2010s has been described in ancient texts about sea creatures as early as two millennia ago, new research suggests.

“In 2011, Bryde’s whales in the Gulf of Thailand were first observed at the surface of the water with their jaws open at right angles, waiting for fish to swim into their mouths. Scientists termed the unusual technique, then unknown to modern science, as ‘tread-water feeding.’ Around the same time, similar behavior was spotted in humpback whales off Canada’s Vancouver Island, which researchers called ‘trap-feeding.’

“In both behaviors the whale positions itself vertically in the water, with only the tip of its snout and jaw protruding from the surface. Key to the technique’s success, scientists believe, is that fish instinctively shoal toward the apparent shelter of the whale’s mouths.

“Flinders University scholars now believe they have identified multiple descriptions of the behavior in ancient texts, the earliest appearing in the Physiologus – the Naturalist – a Greek manuscript compiled in Alexandria around 150-200CE.

“Dr John McCarthy, a maritime archaeologist at Flinders University in Adelaide, South Australia, and the study’s lead author, made the discovery while reading Norse mythology, about a year after he had seen a video of a whale tread-water feeding.

“He noted that accounts of a sea creature known as hafgufa seemed to describe the feeding behavior. ‘It really was a coincidence,’ McCarthy said.

“The most detailed description appeared in a mid-13th-century Old Norse text known as Konungs skuggsjá – the King’s Mirror. It reads: ‘When it goes to feed … the big fish keeps its mouth open for a time, no more or less wide than a large sound or fjord, and unknowing and unheeding, the fish rush in in their numbers. And when its belly and mouth are full, [the hafgufa] closes its mouth, thus catching and hiding inside it all the prey that had come seeking food.’

“The King’s Mirror was an educational text used for explaining the world to young people, McCarthy said. ‘They exaggerate the size … [but] it’s not a fantastical description with any kind of supernatural elements.’ …

” 1986 analysis of the King’s Mirror had found correlations between 26 Old Norse descriptions and scientifically recognized marine animals, but had concluded that the hafgufa ‘must be relegated to the world of the miraculous.’

“ ‘The hafgufa was frustrating for these scholars because they couldn’t quite figure out any animal that this matched to,’ McCarthy said. …

“In the Naturalist – a 2,000-year-old text that ‘preserves zoological information brought to Egypt from India and the Middle East by early natural historians like Herodotus, Ctesias, Aristotle and Plutarch’ – the ancient Greeks referred to the creature as aspidochelone.

“A surviving version of the text reads: ‘When it is hungry it opens its mouth and exhales a certain kind of good-smelling odor from its mouth, the smell of which, once the smaller fish have perceived it, they gather themselves in its mouth. But when his mouth is filled with diverse little fish, he suddenly closes his mouth and swallows them.’ …

“Bryde’s whales and humpbacks are both rorquals, a type of baleen whale. The study was published in the journal Marine Mammal Science.”

More at the Guardian, here. No firewall. Donations encouraged.

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Photo: Ismoon
The earliest recognized form of “written” communication may have been small bits of clay, called tokens. This charming one is from the Indus Valley.

Nowadays, one reads almost too much about artificial intelligence, AI. I myself have an ever increasing list of things I’d rather not have AI managing for me. But using it to translate ancient texts is one application that seems to make perfect sense.

Ruth Schuster writes at Haaretz, “Understanding texts written using an unknown system in a tongue that’s been dead for thousands of years is quite the challenge. Reconstructing missing bits of the ancient text is even harder. …

“Filling in missing text starts with being able to read and understand the original text. That requires much donkey work. Now an Israeli team led by Shai Gordin at Ariel University in the West Bank has reinvented the donkey in digital form, harnessing artificial intelligence to help complete fragmented Akkadian cuneiform tablets.

“Their paper, ‘Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks,’ was published in the Proceedings of the National Academy of Sciences in September.

“ ‘Neural networks’ … means software inspired by biological nervous systems. The concept dates back more than 70 years. … The base concept is to teach machines to learn, think and make decisions. In this case, the computer decides on the plausible completion of missing text. …

“Gordin and the team feed their machine transliterations of the extant Babylonian texts i.e., what the text would have sounded like.

“Then what? When it comes to missing bits in a papyrus or tablet, humans can intuit that “’…ow is your moth…’ isn’t a query into the well-being of your mothball.

With machines, it’s all about mathematics and probabilities based on knowledge gained so far. …

“It may have been trading that inspired the earliest recognized form of communication: ‘pseudo-writing’ on small bits of clay in Mesopotamia around 7,000 years ago. The clay bits, called tokens, were shaped into simplistic imagery such as a cow or other ancient commodities. …

“Then we start seeing abstract signs; repetitive strokes or depressions are interpreted as numbers (price, perhaps); and possibly also personal names, using the first sounds of different imprints to put together words you can’t draw. …

“Anyway, after pseudo-writing came proto-writing: figurative proto-cuneiform inscribed on tablets, which arose about 5,500 years ago in the city of Uruk. … Within mere centuries, proto-cuneiform evolved to become increasingly schematic and Sumer was apparently where it happened, [Gordin] says. And figurative hieroglyphic script began to appear in ancient Egypt at about the same time, about 5,000 years ago. …

“By the time cuneiform became a thing, writing had passed the stage of ‘Sheep : four : Yerachmiel’ and reached the stage of official records, letters and formulaic recounts of the wondrousness of the ruler. …

“For cuneiform, we have the gargantuan multilingual text at Behistun, Iran. Darius the Great had his exploits described in three different cuneiform scripts. [The] Behistun text was monumental: 15 meters (49 feet) high by 25 meters wide, and 100 meters up a cliff on the road connecting Babylon and Ecbatana, all to describe how Darius vanquished Gaumata and other foes. …

“And over decades, linguists slowly interpreted the languages of Babylon and Assyria, thanks to Darius’ monumental ego. …

“Interpreting a dead language is a mathematical game, Gordin says. … Neural networks are a computerized model that can understand text. How? They turn each symbol or word into a number, he explains. …

“When humans reconstruct missing text, their interpretation may be subjective. To be human is to err with bias, and quantifying the likely accuracy of the completion is impossible. Enter the machine. …

“The machine proved capable of identifying sentence structures – and did better than expected in making semantic identifications on the basis of context-based statistical inference, Gordin says. Its talents were further deduced by designing a completion test, in which the machine-learning model had to answer a multiple-choice question: which word fits in the blank space of a given sentence.”

Not sure how many readers are into that kind of thing, but I do find it intriguing. More at Haaretz, here.

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