iiinova — where your digital self keeps evolving

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Vanta 🫐 @vantabats.bsky.social · 25/08/2026

🎉 2k FOLLOWERS ART RAFFLE 🎉 Thank you so much for your support; it’s raffle time! 1 winner will receive a full body drawing! NSFW is permitted. TO ENTER: - Follow me! - ❤️ + 🔄 - Comment your character ref! Ends one week from now! Good luck!

2k followers art raffle. August 25th, 2026 to September 1st, 2026

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Joey 🩺🐲 @joeyillustrated.bsky.social · 23/10/2025

ears so big he can hear your thoughts

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ShayDa 🔞 @shaydahot.bsky.social · 24/10/2025

Eevee butt com I got to work on :3

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The Fluff Dad (🎂 17th) @sandalf.fluff.dad · 25/10/2025

New art! When it's time to call it a day but there's still holes to fill. Art by @skullying.bsky.social #NSFW #Art #FurryArt FA: www.furaffinity.net/view/62758893/

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Fulltime HTML Programmer @programmerhumor.bsky.social · 08/10/2023

iBetThisHaveNotBeenPostedBefore

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pyjyamas @pyjyamas.bsky.social · 20/11/2024

wagon but 💦 forgive me for posting this like, 3 times now

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pyjyamas @pyjyamas.bsky.social · 18/11/2024

wagon (wife dragon)

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pyjyamas @pyjyamas.bsky.social · 27/11/2024

what follows

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rafa_br34 @r34.bsky.social · 09/06/2024

Testing different optimizers on a DCGAN (bitrate is shit cuz youtube) www.youtube.com/watch?v=Ropw...

youtube.com

DCGAN MNIST, SGD optimizer vs Adam optimizer

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.hackbase @hackbase.bsky.social · 16/05/2024

Linux File System

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.hackbase @hackbase.bsky.social · 11/05/2024

RJ45 explained

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.hackbase @hackbase.bsky.social · 12/04/2024

Search engines for pentesters

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Annalee Newitz @annaleen.bsky.social · 12/03/2024

I call Elon Musk's social media platform "X" because I want to remind people that Twitter is gone. We can't make it "ours" again by calling it Twitter. It was never a public space, which is why one edgelord billionaire could kill it. Beware of privately-owned spaces that masquerade as town squares.

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andrea wen-yi wang @andreawwenyi.bsky.social · 21/02/2024

How do LLMs represent relationships between languages? By studying the embedding layers of XLM-R and mT5, we find they are highly interpretable. LLMs can find semantic alignment as an emergent property! Joint work with @dmimno.bsky.social. 🧵

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Natsuakai @natsuakai.bsky.social · 13/12/2023

I FORGOT TO POST PINKZILLA HERE!

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rafa_br34 @r34.bsky.social · 16/12/2023

Was bored so I decided to make this www.shadertoy.com/view/DlVfWR

shadertoy.com

Shadertoy

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D.J. WEED PIZZA @djweedpizza.gobirds.online · 28/11/2023

RIP to the Cybertruck. It takes a true genius to ask the question "what if an El Camino sucked ass and you also couldn't mass produce them?"

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folk tune stan account 🎻 @folktunes.bsky.social · 08/12/2023

pleased to report Frankenstein's monster has turned on its creator

Musk's AI roasting the fuck out of him. It's mostly the kind of mid insult you'd expect but in a rare move it's actually got some bangers in there. Full transcript in comments.

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Parker Seegmiller @pkseeg.bsky.social · 13/11/2023

First post! My recent work (w/Sarah Preum) in developing a statistical depth for texts has been accepted at #EMNLP2023. Our depth orders texts along a singular axis for things like outlier detection, representative example selection, and significance testing. arxiv.org/abs/2310.15010

Graphic showing how TTE depth can perform outlier detection.

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Jennifer Ouellette @jenlucpiquant.bsky.social · 27/09/2023

Einstein right again: Antimatter falls “down” due to gravity like ordinary matter. CERN's ALPHA experiment confirms matter and antimatter react to gravity in a similar way. arstechnica.com?p=1971331

arstechnica.com

Einstein right again: Antimatter falls “down” due to gravity like ordinary matter

CERN's ALPHA experiment confirms matter and antimatter react to gravity in a similar way.

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Programmer Humor @404.bsky.social · 26/07/2023

Ghost in the shell.

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Funny Of Internet @888.bsky.social · 02/09/2023

is it twitter or x ?? make up ur mind

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Naomi Saphra @nsaphra.bsky.social · 21/08/2023

New paper on using interpretable classical ML techniques to understand the training of deep nets! We model grokking effects across random seeds. The plots are VERY pretty. arxiv.org/abs/2308.09543

One-layer transformer trained on modular addition. The first edge that a training run takes to
exit the initialization state 1 significantly impacts the number of epochs the run takes to generalize. We
sort features from most to least important by inverting the learned covariance matrices of each state, and
we define edges by subtracting the learned means between states. The changes in the chart are the top three differences in learned means, sorted
by importance–for example, state 2 has a learned L2 norm that is 0.59 standard deviations lower than state
1, and the L2 norm is the most important feature for state 2.

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