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forloop (@forloopcodes) profile picture

forloop

@forloopcodes

hypergamy climber at aftermatter corp. (https://xitter.twitterapi.xyz/t.co/e7TqX6aab0), shrike ⚡︎, contextplus (2k) and cargo install safeinstall. forloop@poke.com

 college wifi torrent seeder
github.com/forloopcodes
Joined September 2024
  • Tweets28K
  • Following2.2K
  • Followers9.7K
2.2KMedia
Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)Photo by forloop (@forloopcodes)
Sure! Here's how the tightest (known) packing of 67, 6767 and 676767 squares in a larger square looks like: I made the most optimized algorithm to find out the tightest packing of n smaller squares in a larger square test it out: forloopcodes.github.io/least… (runs on your gpu) more details: input: n (number of squares) intermediate: s (side length) output: [[x, y, angle]*n] (array of position of each square) solver (squarepack): pack(n) returns (s, [[x, y, angle], …]) scale: n=100000 in about 4 s, 0.08 s in browser, n=1000001 in 0.2 s. verifier: p_ij = ½ + (|cos φ| + |sin φ|)/2 − max_a |a·(c_i − c_j)|, φ = θ_j − θ_i flow: 1. best of all in O(n): Grid ⌈√n⌉, Göbel strip/square families, L-extensions, the √7 family, DeVincentis,Wainwright 19, Schadt 50/171 2. cache lookup 3. tilted-block search: p×q block rotated 45°, remaining space filled by walls anchoring 4. numerical compaction: Penalty energy E = Σ max(0,penetration)² + Σ max(0,protrusion)², analytic gradient, L-BFGS, shrink s by bisection, basin-hopping. github: github.com/forloopcodes/leas…
Image from forloop (@forloopcodes)
Image from forloop (@forloopcodes)
Image from forloop (@forloopcodes)
Dersu (@tak3sh8) profile pictureDersu@tak3sh8Sep 1
I'm sure you always wanted to know how the tightest (known) packing of "n" squares within a larger square looks like... 😍
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Arnav (@__iamarnav) profile picture
Arnav@__iamarnav4h
at least, it wasn't exactly ai that took his job
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ok looks like Jensen maybe out now
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@ThePrimeagen
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BREAKING: NVIDIA CEO Jensen Huang resigns
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Jensens downfall is drazy
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largest bank of india btw
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damn
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no not you too 😭😭 you cant just say that with a straight face and list my blog as the source 😭😭😭
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Rebane (@rebane2001) profile pictureRebane@rebane200116h
okay so even after writing a blog post about how i did not actually get a million dollars there are still ai-generated news articles coming out claiming i did EXCEPT NOW THEY ALSO LINK TO MY BLOG AS THE SOURCE???????
Lyra Rebane reports $1.33 million Google Chrome bounty Lyra Rebane said on her blog that Google paid her $1,333,337 on Nov. 7, 2026, for a critical Chrome security flaw, pushing her reported earnings past $1 million. Lyra Rebane reported on her blog that Google awarded her $1,333,337 on Nov. 7, 2026, for a critical security flaw in Google Chrome. She wrote that the payment pushed her net worth past $1 million. A record single payout The post describes the Nov. 7 award as a single bounty payout of $1,333,337. Rebane tied the milestone to her work as a security researcher and her history of reporting browser vulnerabilities.

ALT Lyra Rebane reports $1.33 million Google Chrome bounty Lyra Rebane said on her blog that Google paid her $1,333,337 on Nov. 7, 2026, for a critical Chrome security flaw, pushing her reported earnings past $1 million. Lyra Rebane reported on her blog that Google awarded her $1,333,337 on Nov. 7, 2026, for a critical security flaw in Google Chrome. She wrote that the payment pushed her net worth past $1 million. A record single payout The post describes the Nov. 7 award as a single bounty payout of $1,333,337. Rebane tied the milestone to her work as a security researcher and her history of reporting browser vulnerabilities.

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vaguepost god is when i write an entire blog post explaining in detail what happened
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@rebane2001
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Image from forloop (@forloopcodes)
Image from forloop (@forloopcodes)
hibakod (@hibakod) profile picturehibakod@hibakodNov 11
Post your proudest block below
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turkish men are usually chill why did he block you?
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only the one with red pfp
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"github copilot is free for students (auto model selection only)" son im crine
Image from Bob 🇪🇺 (@libobral)
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Is deepseek free better?
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not good but better than luna
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if you’re in paris you may be able to catch me and get the new helium stickerpack allegedly
Image from wukko (@uwukko)
wukko (@uwukko) profile picturewukko
@uwukkoNov 11
successfully moved to paris
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can i get one 👉👈
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forloop retweeted
V12 (@v12sec) profile picture
V12
@v12secNov 11
Any telegram message can now become RCE 6630b003766baed1fa86cea880d22e41dc416f63d800de3246941ede2396ad48
Pavel Durov (@durov) profile picturePavel Durov
@durovNov 10
Any Telegram message can now become an app. ⚡ Downloads instantly (less than 4 KB)
🎨 Interactive and natively rendered
💸 Payments and viral mechanics built in 🛠️ Build your own. More info and docs for devs: t.me/BotNews/122
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imagine if google colab had intellisense and code documentation and not gemini
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i hacked a cli and just let my clancker deal with that shit
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😭
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to the guy who bookmarked it PLEASE I BEG YOU I WILL PAY FOR IT
Image from forloop (@forloopcodes)
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okay windows search is actually getting better, infact its the fastest ever
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HOLY MOTHER OF GOOD NEWS pls let it work let it work let it work this post will remain vague until I get the OK to be excited publicly but YAAAAAAAY
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emploid
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Fable is right more often than Carbon, but Carbon is wrong less often than Fable *according to omniscience
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what are the chances that the model made up a correct answer without actually knowing it
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forloop retweeted
spectre (@Medfa1222) profile picture
spectre@Medfa1222Nov 10
sigh
Image from spectre (@Medfa1222)
CG (@cgtwts) profile pictureCG
@cgtwtsNov 9
holy shit, this is literally AGI.
Image from CG (@cgtwts)
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Introducing e-means, an algorithm beating k-means in 10x fewer epochs. With order of magnitude wall-clock speedups, e-means is released in FAISS and needs no hyperparameter tuning beyond k. It is robust to various scales and datasets. Still skeptical ? Just try e-means [1/10]🧵
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i might sound dumb but is it like comparing mcts with alpha beta?
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aura monster
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