May 1, 2026 05:57 PM
(This post was last modified: May 1, 2026 05:58 PM by C C.)
Universal patterns emerge in human languages, revealing “four surprising laws” behind their evolution
https://thedebrief.org/universal-pattern...evolution/
EXCERPTS: Human languages as disparate as English, Japanese, and Russian follow remarkably similar evolutionary paths, according to a new AI study, which investigated how new concepts were added over time.
Researchers from Fudan, Harvard, and Stony Brook Universities revealed their findings in a recent paper published in the Proceedings of the Royal Society B, based on their work across 21 languages, many of which are separated by time, going back to the medieval period, as well as distance.
[...] “We were inspired by the idea that AI technologies for representing language semantics (word embeddings) give us a rigorous way to reason about the evolution of language,” Dr. Skiena said. “With word embeddings, each distinct vocabulary is associated with a particular point in a high-dimensional feature space. Words with similar meanings are represented by nearby points.”
“In essence,” Dr. Skiena continued, “our paper asks how the vocabulary of languages distributed in this feature space, and what kind of mathematical process would create a similar distribution.”
[...] The challenge was producing a model that captured how real languages evolve. “We wanted to prove that certain mathematical models generated embedding spaces that look very much like real natural languages,” Dr. Skiena said. “But what do real natural languages look like?”
“We had to develop a set of four surprising laws/principles that govern the structure of real languages,” Dr. Skiena added, “and then prove that our favored mathematical model generates embedding spaces that also had these unusual properties.”
“I think of cultural influences as the force that shapes the evolution of languages, but it is clear that the brain shapes these cultural influences,” Dr. Skiena said, regarding the similarities the researchers found among different languages. Co-author Dr. Sergiy Verstyuk added, in a conversation with The Debrief, that although there are potential connections between their work and neuroscience studies, that was not the direct aim of their work.
Among the commonalities the researchers discovered was that popular words were often clustered with other popular words in specific regions of the mathematical space. Additionally, the hierarchy of this type of clustering was quite similar between many languages. Word creation usually occurred in bursts, with recent words surrounding other recent words, as new concepts entered the vernacular, similar to the periodicity of rapid change in biological evolution... (MORE - missing details)
https://thedebrief.org/universal-pattern...evolution/
EXCERPTS: Human languages as disparate as English, Japanese, and Russian follow remarkably similar evolutionary paths, according to a new AI study, which investigated how new concepts were added over time.
Researchers from Fudan, Harvard, and Stony Brook Universities revealed their findings in a recent paper published in the Proceedings of the Royal Society B, based on their work across 21 languages, many of which are separated by time, going back to the medieval period, as well as distance.
[...] “We were inspired by the idea that AI technologies for representing language semantics (word embeddings) give us a rigorous way to reason about the evolution of language,” Dr. Skiena said. “With word embeddings, each distinct vocabulary is associated with a particular point in a high-dimensional feature space. Words with similar meanings are represented by nearby points.”
“In essence,” Dr. Skiena continued, “our paper asks how the vocabulary of languages distributed in this feature space, and what kind of mathematical process would create a similar distribution.”
[...] The challenge was producing a model that captured how real languages evolve. “We wanted to prove that certain mathematical models generated embedding spaces that look very much like real natural languages,” Dr. Skiena said. “But what do real natural languages look like?”
“We had to develop a set of four surprising laws/principles that govern the structure of real languages,” Dr. Skiena added, “and then prove that our favored mathematical model generates embedding spaces that also had these unusual properties.”
“I think of cultural influences as the force that shapes the evolution of languages, but it is clear that the brain shapes these cultural influences,” Dr. Skiena said, regarding the similarities the researchers found among different languages. Co-author Dr. Sergiy Verstyuk added, in a conversation with The Debrief, that although there are potential connections between their work and neuroscience studies, that was not the direct aim of their work.
Among the commonalities the researchers discovered was that popular words were often clustered with other popular words in specific regions of the mathematical space. Additionally, the hierarchy of this type of clustering was quite similar between many languages. Word creation usually occurred in bursts, with recent words surrounding other recent words, as new concepts entered the vernacular, similar to the periodicity of rapid change in biological evolution... (MORE - missing details)