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@BienCePasser

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Baie de Sufokia Katılım Mart 2020
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ADIN
ADIN@ADINresearch·
Had a Jane Street interview in 2014 Round 7. Interviewer says 'meet me at Washington Square Park, southwest corner, 2 PM.' I show up. He's playing chess with a guy who's clearly hustling tourists. Interviewer's losing badly. Without looking up he says, 'Take my position.' I sit down. The chess hustler looks at me and grins. 'Your boy owes me $40. You covering his position?' I look at the interviewer. He nods. 'Assume the debt,' he says. 'Now optimize.' I study the board. I'm down a queen and two rooks. Completely hopeless. 'This position is unwinnable,' I say. 'Correct. Now make it profitable.' 'What?' The chess hustler is getting impatient. 'You playing or what, kid?' The interviewer slides me a $20. 'Market make this game.' I'm confused. 'How do I market make chess?' 'Bid-ask on the number of moves until checkmate. Hustler takes the under, you take the over. Spread is your edge.' I look at the position again. Maybe 8 moves max until I'm mated. 'I bid 12 moves, offer 15,' I announce. The hustler laughs. 'I'll take the under on 12 all day.' 'Done,' says the interviewer. 'You're now short volatility on a deterministic outcome.' Three moves later I'm checkmated. I owe the hustler $40 plus my $20 bet. 'How confident were you in that 12-move bid?' the interviewer asks. '0.95,' I say, because that's what you always say. '0.95 huh?' He chuckles. 'You just sold insurance on the Titanic.' He stands up. 'The real trade was shorting your confidence and going long on the hustler's experience. You missed the obvious hedge: offering chess lessons to tourists at $25/hour while the game played out.' 'But I don't know how to play chess well enough to teach.' 'Exactly. That's called selling vol you don't have. Very Jane Street.' Offer rescinded. Reason: 'Failed to recognize that the park itself was the market and the pigeons were the only rational actors.'"
Deedy@deedydas

Jane Street made ~$40B in 2025 with 3,500 employees, a ~2x from the year before. At ~65-70% profit margin, that's $8M profit / employee, the highest for a 1000+ ppl company. High-frequency trading continues to be the most efficient money making engine. I want to share an old story about my Jane Street interview in 2014. Jane Street was known for hiring a lot of math, physics and CS olympiad winners from top universities and putting them through many rounds - including, for trading roles, a gauntlet of mental math. It was my 6th interview and my final round and I recall being asked "What is the next day after today in DD/MM/YYYY where all the digits are unique?" They'd toy with you and say "You can use a pencil and paper, if you want" but you knew that was an instant no. Painstakingly and as quickly as I could, I came to an answer. "How confident are you that this is correct on a 0-1 probability scale?" the interviewer said. "0.95", I blurted out, not fully knowing how to answer that. "Are you sure?" After thinking harder for a few more seconds, I realized I could've flipped the digits around to get a closer date. I gave the interviewer my answer. It was correct. "0.95 huh?" he chuckled. That's when I knew I failed. Note: fwiw, other companies that come close in efficiency are - Tether ($90M+ profit/emp) - Hyperliquid ($80M+ profit/emp) and on revenue: - Valve ($50M/emp) - OnlyFans ($37M/emp) - Craigslist ($14M/emp) - Anthropic ($12M/emp, run rate) - OpenAI ($8M/emp, run rate) For comparison, Nvidia is very efficient at scale and is $4.4M/emp.

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trash
trash@trashh_dev·
me and my llm trying to find an entry level software engineer position
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Yann LeCun
Yann LeCun@ylecun·
Dario is wrong. He knows absolutely nothing about the effects of technological revolutions on the labor market. Don't listen to him, Sam, Yoshua, Geoff, or me on this topic. Listen to economists who have spent their career studying this, like @Ph_Aghion , @erikbryn , @DAcemogluMIT , @amcafee , @davidautor
TFTC@TFTC21

Anthropic CEO Dario Amodei: “50% of all tech jobs, entry-level lawyers, consultants, and finance professionals will be completely wiped out within 1–5 years.”

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Rémi Mathis
Rémi Mathis@RemiMathis·
On appelle "effet Dunning-Kruger au carré" le fait de penser savoir ce qu'est l'effet Dunning-Kruger, en faire une émission de radio... et de se tromper à son sujet En réalité, les compétents sont plus sûrs d'eux - c'est seulement la *différence assurance-compétence* qui diminue
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Aakash Gupta
Aakash Gupta@aakashgupta·
PewDiePie didn’t “train his own LLM.” He fine-tuned an existing open-source model on coding benchmarks. His model started at 8%, crawled to 16% after format fixes, and one run hit 19.6% that briefly passed GPT-4o on a single benchmark before he couldn’t consistently reproduce it. The tweet makes it sound like a YouTuber casually built a frontier lab in his bedroom. What actually happened is more interesting: a guy with a $41,000 home rig of 10 GPUs and 424GB of VRAM spent months failing, retraining, and iterating on dataset quality until he squeezed marginal gains out of a fine-tune. This is the part worth paying attention to. The entire arc from October 2025 to now tells you where AI tooling has actually landed. PewDiePie went from building his first PC to running Qwen 235B locally, vibe-coding a custom chat UI, orchestrating multi-agent voting systems, and now fine-tuning models on custom datasets. He did most of this through AI-assisted coding itself. The video is literally called “I wish I never did this project.” He’s documenting how painful and tedious the process was. That honesty is the signal. The hype accounts strip that away and replace it with “what the f*ck, YouTuber beats DeepSeek.” The real takeaway: fine-tuning on specific benchmarks with curated data can let anyone temporarily spike a score past models that cost hundreds of millions to train. That tells you everything about how narrow benchmark gaming has become, and nothing about general capability. PewDiePie knows this. The people quote-tweeting him with shock emojis do not.
sui ☄️@birdabo

pewdiepie just trained his own LLM. his model outperformed deepseek v2.5, LLAMA-4 and GPT-4o in coding benchmark. what the f*ck.

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Neil Zeghidour
Neil Zeghidour@neilzegh·
Me defending my O(n^3) solution to the coding interviewer.
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༒︎
༒︎@offprozac·
accidentally isolated myself for years
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Cursed
Cursed@CursedVideos·
France is a real country
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jeanne d'larp 🦋🔆
jeanne d'larp 🦋🔆@ourmartyredlady·
the exact moment you start thinking this you Simply must do everything in your power to change course else its gonna snowball into much worse things
「Indigo」⚢@FoolPlanet

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Ramp Capital
Ramp Capital@RampCapitalLLC·
gm
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goosewin
goosewin@Goosewin·
a sign of true evil
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kijz
kijz@kijzYAP·
underrated S tier programming skill: actually reading the fucking error message
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Matt Allen
Matt Allen@investmattallen·
This is wild 🤯
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