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Mason Youngblood

Профиль Vively

Postdoc fellow researching cultural evolution at the Institute for Advanced Computational Science - Electronic music as Callosum - masonyoungblood.com

Thanks Hendrik! Hope it can get resolved too 🤞

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The irony of looking for help with this on Bluesky is not lost on me! 😂

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@sobchuk.bsky.social and I also wrote an intro outlining this emerging field—exciting to see just how much its expanded in the last decade, even exhibiting clusters corresponding to subfields (e.g., big data, cultural phylogenetics, film and literature, etc.)! www.doi.org/10.1017/ehs....

Cultural evolution – of the arts | Evolutionary Human Sciences | Cambridge CoreCultural evolution – of the arts - Volume 8www.doi.org
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Thanks Pat!! :)

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Oh amazing! So happy to hear it was easy to use

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This began in 2021 when I tweeted about the cultural evo of climbing and @sampassmore.bsky.social DMed me! So excited to see it out after 4 years of statistical binges and brick walls—I literally had to learn deep learning to finish it 😅 @royalsocietypublishing.org @culturalevolsoc.bsky.social

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I've tested it with birds, bats, whales, chimpanzees, and humans, and it's recovered meaningful structure in all cases. I'll expanding it in the coming months/years so if you have any features you'd like to see just hit me up! 😊 Here's the preprint: doi.org/10.48550/arX...

chatter: a Python library for applying information theory and AI/ML models to animal communicationThe study of animal communication often involves categorizing units into types (e.g. syllables in songbirds, or notes in humpback whales). While this approach is useful in many cases, it necessarily f...doi.org
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The library provides an end-to-end workflow—from preprocessing and segmentation to model training and feature extraction—that enables researchers to quantify features like complexity, predictability, similarity, and novelty.

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By leveraging a variety of different architectures, including variational autoencoders and vision transformers, chatter represents vocal sequences as trajectories in high-dimensional latent space, bypassing the need for manual or automatic categorization of units.

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Congrats @alexeykoshevoy.bsky.social!!!

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I totally understand, and thanks for the apology. Always down to chat about this stuff—I know there's a lot to debate about these patterns in other species (and how meaningful they actually are in general). All the best to you as well!

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Do I see that the data for hybrids, which has a minor role in the paper and the smallest N, is v noisy? 100%, I have eyes. But a trend line is only a coarse summary, especially when accounting for other sources of variation. More in the paper if you decide to check your ego and stop projecting. 🙂

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Wow okay. Sorry I thought I was dealing with an adult. Maybe you should read the paper before making aggressive critiques... That line of best fit comes from a model explicitly based on the mathematical formulation of Menzerath's law, accounting for individual identity and sequence ID...

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What is your specific critique? I don't see any red flags with the plots, especially given the output of the models.

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Congrats!! 👏

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