Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

a guy who got fired from a prop desk for "not being fast enough" now runs a trading agent that closes positions faster than the guys who fired him he wasn't slow at reading charts. he was slow at the part nobody talks about - rebuilding a strategy after...

L1vsun's profile picture

Livsun

4,285 subscribers

12,021 görüntüleme • 7 gün önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Jane Street spent $6 billion and 4,032 GPUs on one thing: AI agents that loop through trading strategies 100x faster than any human. Generate, backtest, kill, repeat - thousands a week, until one survives data it's never seen. That loop is why they made $39.6 billion last year while 89% of retail went broke trading one idea they never stress-tested. The edge was never a smarter idea. It was volume. They test 100 strategies for every 1 you test by hand, and a second agent kills the 97 that only look good on old data before a dollar goes live. Now the entire loop fits in a chat box. Horizon takes one plain-English sentence and spins up the same two agents. One builds your strategy, one tries to kill it - backtests 5 years in seconds, and only what survives goes live on your exchange. The $150 billion setup. Free while beta open. Bookmark this & read the full breakdown below - the exact two-agent loop, step by step, and who just handed it to retail.
0:46

Jane Street spent $6 billion and 4,032 GPUs on one thing: AI agents that loop through trading strategies 100x faster than any human. Generate, backtest, kill, repeat - thousands a week, until one survives data it's never seen. That loop is why they made $39.6 billion last year while 89% of retail went broke trading one idea they never stress-tested. The edge was never a smarter idea. It was volume. They test 100 strategies for every 1 you test by hand, and a second agent kills the 97 that only look good on old data before a dollar goes live. Now the entire loop fits in a chat box. Horizon takes one plain-English sentence and spins up the same two agents. One builds your strategy, one tries to kill it - backtests 5 years in seconds, and only what survives goes live on your exchange. The $150 billion setup. Free while beta open. Bookmark this & read the full breakdown below - the exact two-agent loop, step by step, and who just handed it to retail.

cvxv666

317,059 görüntüleme • 1 ay önce

Ken Griffin, CEO of Citadel, said: "I'm fairly depressed watching AI do a week of PhD work in a few hours" He's worth $51.2 billion and 20% of every stock trade in America goes through his firm. The money isn't what's bothering him. Citadel pays $400,000 to $650,000 a year for that work. New trading AI agent does it now, on a free trial, for people who have never written a line of code. It went live this summer and most of your timeline still hasn't noticed. You type one sentence in plain English. AI agents loop takes it from there: > an AI agent turns your sentence into a real trading strategy > backtests it across 5 years of data in about 12 seconds > scores it 0 to 100 and shows you the exact spot where it leaks > kills the versions that only look good on paper > rebuilds what's left and runs the loop again > stress-tests the survivor on years it has never seen, then puts it live on your exchange in about 90 seconds That list is the entire job description of a junior quant. At a desk, one properly tested idea burns about $87,500 in salary time, and most of what they build is dead by week six. Two clicks and this AI agent is testing your own idea. Costs you nothing and it runs the whole thing by itself: Griffin gets to be depressed about it. He already owns the desk. You just got handed one. Bookmark & read full story of how they got an AI to build trading strategies and kill its own bad ones is in the article below.
0:45

Ken Griffin, CEO of Citadel, said: "I'm fairly depressed watching AI do a week of PhD work in a few hours" He's worth $51.2 billion and 20% of every stock trade in America goes through his firm. The money isn't what's bothering him. Citadel pays $400,000 to $650,000 a year for that work. New trading AI agent does it now, on a free trial, for people who have never written a line of code. It went live this summer and most of your timeline still hasn't noticed. You type one sentence in plain English. AI agents loop takes it from there: > an AI agent turns your sentence into a real trading strategy > backtests it across 5 years of data in about 12 seconds > scores it 0 to 100 and shows you the exact spot where it leaks > kills the versions that only look good on paper > rebuilds what's left and runs the loop again > stress-tests the survivor on years it has never seen, then puts it live on your exchange in about 90 seconds That list is the entire job description of a junior quant. At a desk, one properly tested idea burns about $87,500 in salary time, and most of what they build is dead by week six. Two clicks and this AI agent is testing your own idea. Costs you nothing and it runs the whole thing by itself: Griffin gets to be depressed about it. He already owns the desk. You just got handed one. Bookmark & read full story of how they got an AI to build trading strategies and kill its own bad ones is in the article below.

cvxv666

222,320 görüntüleme • 13 gün önce

Ken Griffin built Citadel into $67B fund and hires PhDs out of Stanford and MIT. He watched agentic AI do their month work in an afternoon and admitted it sent him home depressed. The interesting bit is what he was describing. A six-part research loop. Find, code, test, deploy, autopsy, learn. Five of those six are done. Free. Available tonight. Prompt to backtested strategy in 12 seconds. Prompt to live broker in 90. The Greenwich quant doing that same work costs $650,000 a year and clears one hypothesis a month. The sixth exists nowhere. Not at Citadel, not at Man Group, not in any repo. It's the part where the machine remembers what already failed. Every losing test dies in a log file. The next agent starts blind. Negative results are the most valuable data in quant research and literally nobody stores them. This loop broken down in my article below. Read it before someone builds the last one and stops explaining how.
0:51

Ken Griffin built Citadel into $67B fund and hires PhDs out of Stanford and MIT. He watched agentic AI do their month work in an afternoon and admitted it sent him home depressed. The interesting bit is what he was describing. A six-part research loop. Find, code, test, deploy, autopsy, learn. Five of those six are done. Free. Available tonight. Prompt to backtested strategy in 12 seconds. Prompt to live broker in 90. The Greenwich quant doing that same work costs $650,000 a year and clears one hypothesis a month. The sixth exists nowhere. Not at Citadel, not at Man Group, not in any repo. It's the part where the machine remembers what already failed. Every losing test dies in a log file. The next agent starts blind. Negative results are the most valuable data in quant research and literally nobody stores them. This loop broken down in my article below. Read it before someone builds the last one and stops explaining how.

cvxv666

128,353 görüntüleme • 9 gün önce

While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:
0:53

While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:

cvxv666

53,163 görüntüleme • 1 ay önce

A guy put a mini PC on his desk and runs a wall of faceless YouTube channels from it. The box is the size of a paperback. Sits next to his coffee. He plugged it in and that was it. Now every channel on his screen uploads on schedule without him. He doesn't film. He doesn't edit. He doesn't even open YouTube most days. He says one channel lands him around $8,000 a month. He scrolled past dozens just now. The box paid for itself in 3 days. His rent is now fully paid by a box on his desk. The crazy part is regular people are quietly becoming media networks. Save this, you are watching the next gold rush hit the home office.
0:30

A guy put a mini PC on his desk and runs a wall of faceless YouTube channels from it. The box is the size of a paperback. Sits next to his coffee. He plugged it in and that was it. Now every channel on his screen uploads on schedule without him. He doesn't film. He doesn't edit. He doesn't even open YouTube most days. He says one channel lands him around $8,000 a month. He scrolled past dozens just now. The box paid for itself in 3 days. His rent is now fully paid by a box on his desk. The crazy part is regular people are quietly becoming media networks. Save this, you are watching the next gold rush hit the home office.

Superior

24,476 görüntüleme • 2 ay önce

Godfather of agents showed how he created the loop engineering that everyone now uses: as PhD student, he wrote the formula every AI agent now runs on - his formula taught agents to self-improve here's the formula: step 1 → stop making the model just think OR just act - make it alternate: think → act → observe → think again step 2 → let it reason out loud before every action - the plan guides the next move, not just the output step 3 → feed the result of each action back in - the model reads what happened and adjusts, live step 4 → when it fails, don't restart make it reflect on WHY it failed, in words, then retry with that memory step 5 → store those reflections - the agent gets better across attempts without any retraining before OpenAI, before he ran Tencent's AI - he was a grad student who quietly wrote the blueprint every agent now follows - now give 90-min course watch & bookmark - then read how the agent systems actually works ↓
1:22:01

Godfather of agents showed how he created the loop engineering that everyone now uses: as PhD student, he wrote the formula every AI agent now runs on - his formula taught agents to self-improve here's the formula: step 1 → stop making the model just think OR just act - make it alternate: think → act → observe → think again step 2 → let it reason out loud before every action - the plan guides the next move, not just the output step 3 → feed the result of each action back in - the model reads what happened and adjusts, live step 4 → when it fails, don't restart make it reflect on WHY it failed, in words, then retry with that memory step 5 → store those reflections - the agent gets better across attempts without any retraining before OpenAI, before he ran Tencent's AI - he was a grad student who quietly wrote the blueprint every agent now follows - now give 90-min course watch & bookmark - then read how the agent systems actually works ↓

codila

28,667 görüntüleme • 28 gün önce

ChatGPT can write you a thousand trading strategies from one sentence. 999 will quietly bleed your account dry. Every single one of them looks like a winner. One method pulls the real one out. Quant desks have run it for years. It's called loop engineering. It's not a smarter prompt. It's a loop: generate a strategy, test it, score why it failed, feed that back, and run it again until one survives data it has never seen. Man Group runs $150 billion. They built an AI that writes and tests hundreds of strategies a week. And second agent whose only job is to hunt the ones that secretly overfit and kill them before a cent goes live. > describe an idea -> backtest 5 years in 12 seconds > read why it died -> feed that back in > run it again until one survives data it never saw AI can write a thousand strategies. Loop engineering is the only thing that tells you which one was ever real. 89% of retail lost money in 2025. Almost none of it from bad ideas. All of it from trading the first guess and never running it through backtest loop. Horizon just put the whole thing in a chat box, free while the beta's open: You're not losing to smarter traders. You're losing to the ones who opened the tab. Anyone can generate a strategy now. Almost no one runs the loop that proves it. That gap is the whole edge. You'll mean to check it later. Later is a "waitlist closed" page.
0:43

ChatGPT can write you a thousand trading strategies from one sentence. 999 will quietly bleed your account dry. Every single one of them looks like a winner. One method pulls the real one out. Quant desks have run it for years. It's called loop engineering. It's not a smarter prompt. It's a loop: generate a strategy, test it, score why it failed, feed that back, and run it again until one survives data it has never seen. Man Group runs $150 billion. They built an AI that writes and tests hundreds of strategies a week. And second agent whose only job is to hunt the ones that secretly overfit and kill them before a cent goes live. > describe an idea -> backtest 5 years in 12 seconds > read why it died -> feed that back in > run it again until one survives data it never saw AI can write a thousand strategies. Loop engineering is the only thing that tells you which one was ever real. 89% of retail lost money in 2025. Almost none of it from bad ideas. All of it from trading the first guess and never running it through backtest loop. Horizon just put the whole thing in a chat box, free while the beta's open: You're not losing to smarter traders. You're losing to the ones who opened the tab. Anyone can generate a strategy now. Almost no one runs the loop that proves it. That gap is the whole edge. You'll mean to check it later. Later is a "waitlist closed" page.

cvxv666

173,703 görüntüleme • 1 ay önce

ANTHROPIC LEAD ENGINEER MAKING $2.3M/YEAR JUST LEAKED A 12-PAGE DOCUMENT - AND GOT FIRED 15 MINUTES AFTER PUBLISHING most developers build loops - but almost every loop breaks in one of five ways, and each failure has a symptom visible from the outside without reading a single line of code > Blind loop - the agent waits for a human to hand it work every morning - automating execution but not discovery > Tangled loop - parallel agents share one directory and overwrite each other parallelism that destroys instead of multiplies > Nodding loop - the agent grades its own work and approves it every time a loop that has never said no to itself is broken > Amnesiac loop - results live only in the context window every morning the system wakes up with no memory of yesterday > Manual loop - no trigger a human presses the button to start it that is not a loop that is a script waiting for a person a real loop finds its own work - remembers what it did has something that can say no never lets two agents touch the same file and fires itself on a timer remove any one of the five - and the loop either breaks or never starts 12 pages that changed how I build agentic systems today
0:50

ANTHROPIC LEAD ENGINEER MAKING $2.3M/YEAR JUST LEAKED A 12-PAGE DOCUMENT - AND GOT FIRED 15 MINUTES AFTER PUBLISHING most developers build loops - but almost every loop breaks in one of five ways, and each failure has a symptom visible from the outside without reading a single line of code > Blind loop - the agent waits for a human to hand it work every morning - automating execution but not discovery > Tangled loop - parallel agents share one directory and overwrite each other parallelism that destroys instead of multiplies > Nodding loop - the agent grades its own work and approves it every time a loop that has never said no to itself is broken > Amnesiac loop - results live only in the context window every morning the system wakes up with no memory of yesterday > Manual loop - no trigger a human presses the button to start it that is not a loop that is a script waiting for a person a real loop finds its own work - remembers what it did has something that can say no never lets two agents touch the same file and fires itself on a timer remove any one of the five - and the loop either breaks or never starts 12 pages that changed how I build agentic systems today

Sprytix

153,575 görüntüleme • 1 ay önce

THIS GUY CONNECTED CLAUDE TO TRADINGVIEW AND CUT 200+ HOURS OF MANUAL CHART WORK 40 trades a week used to mean the same loop: open the chart, check RSI, compare EMA, write notes and wait for the next setup now Claude reads TradingView 24/7, tracks volume, indicators and price conditions while he is not even at the desk this is not a $20k trading terminal and not a quant fund setup, just one laptop, one chart and one strategy written in plain English the crazy part is not that Claude predicts the market, it is that a regular trader can remove the boring human loop from every setup ↓
0:26

THIS GUY CONNECTED CLAUDE TO TRADINGVIEW AND CUT 200+ HOURS OF MANUAL CHART WORK 40 trades a week used to mean the same loop: open the chart, check RSI, compare EMA, write notes and wait for the next setup now Claude reads TradingView 24/7, tracks volume, indicators and price conditions while he is not even at the desk this is not a $20k trading terminal and not a quant fund setup, just one laptop, one chart and one strategy written in plain English the crazy part is not that Claude predicts the market, it is that a regular trader can remove the boring human loop from every setup ↓

Gipp 🦅

55,610 görüntüleme • 2 ay önce

"[Lewis Hamilton] was really down on himself. And no one likes to see that because at the end of the day, whether you're a fan or not, Lewis Hamilton is the greatest racing driver we've ever seen." "Statistically, he is the greatest. I think he's the greatest even without the stats." "He wears his heart on his sleeve and should be applauded for that because it does a lot of good when he wears his heart on his sleeve. He did apologise to Rachel Brookes for being so down in the dumps off camera. He said, 'I'm really sorry about that. I'm just so down.' And that just shows the extent that he really was down. He's not putting this on for the cameras, trust me." "And once again, it's right after the race. He's not had time for a debrief. He's not had time to have a chat with his race engineer. So he probably didn't know the extent of whatever damage the car had at the time he spoke to Rachel. And he probably didn't realise that it was the car that was hindering him more so than his driving in that one. And look, when you're in a Ferrari and you're overtaken by Nico Hülkenberg, albeit in a Ferrari powered Sauber, you're going to question, 'is it me really? Am I doing something wrong here?' Because it just didn't go for him really from the outset." [📹 The Fast And The Curious]
1:11

"[Lewis Hamilton] was really down on himself. And no one likes to see that because at the end of the day, whether you're a fan or not, Lewis Hamilton is the greatest racing driver we've ever seen." "Statistically, he is the greatest. I think he's the greatest even without the stats." "He wears his heart on his sleeve and should be applauded for that because it does a lot of good when he wears his heart on his sleeve. He did apologise to Rachel Brookes for being so down in the dumps off camera. He said, 'I'm really sorry about that. I'm just so down.' And that just shows the extent that he really was down. He's not putting this on for the cameras, trust me." "And once again, it's right after the race. He's not had time for a debrief. He's not had time to have a chat with his race engineer. So he probably didn't know the extent of whatever damage the car had at the time he spoke to Rachel. And he probably didn't realise that it was the car that was hindering him more so than his driving in that one. And look, when you're in a Ferrari and you're overtaken by Nico Hülkenberg, albeit in a Ferrari powered Sauber, you're going to question, 'is it me really? Am I doing something wrong here?' Because it just didn't go for him really from the outset." [📹 The Fast And The Curious]

sim 🇧🇷🇲🇽🇸🇳🇫🇷🇭🇹

97,656 görüntüleme • 1 yıl önce

One guy built a wedding camera app in a month and it now makes him over $1,000,000 a year. No team, no investors, no marketing budget. 100,000 downloads in the first month. Zero dollars on ads. He did not bolt marketing onto the product. He made using the product the marketing. You cannot use the app alone. The host has to pull every guest into it. One wedding is not one user. It is 200 people scanning the same code in one evening. The guest liked it at someone else's wedding. A month later he throws his own event and brings his own crowd. The loop spins for free. It does not look like an ad. To the guest it is a gift. So they install it gladly. $2 to $50 subscriptions. 5% pay. That is $100,000 a month. He did not win on budget. He sewed the growth into the product itself. Could you build the loop, or is it just luck?
0:23

One guy built a wedding camera app in a month and it now makes him over $1,000,000 a year. No team, no investors, no marketing budget. 100,000 downloads in the first month. Zero dollars on ads. He did not bolt marketing onto the product. He made using the product the marketing. You cannot use the app alone. The host has to pull every guest into it. One wedding is not one user. It is 200 people scanning the same code in one evening. The guest liked it at someone else's wedding. A month later he throws his own event and brings his own crowd. The loop spins for free. It does not look like an ad. To the guest it is a gift. So they install it gladly. $2 to $50 subscriptions. 5% pay. That is $100,000 a month. He did not win on budget. He sewed the growth into the product itself. Could you build the loop, or is it just luck?

Marlow

513,143 görüntüleme • 1 ay önce

A Chinese mathematician posted a 3 minute video on Bilibili explaining how he lost his $10,000 a month gig to AI. The model he had been training started writing harder math problems than he could invent. He admitted his own mistake in business positioning. He had spent four years hand writing PhD level math problems for Scale AI's reinforcement learning pipeline. $50 to $100 per problem. 200 problems a month. Then synthetic data killed his entire contract category. He was no longer able to invent a problem the machine could not solve. At 2:13 he says the word agent. He says it once. He never says it again in the video. The way he says it is the only thing on screen that did not come off the teleprompter. He has been recording videos off a teleprompter for three months. The teleprompter runs on the same agent that killed his Scale AI work. Every script is generated by Claude. Every word he reads to camera is the agent's. The new job is reading. Someone pulled the script repository from a Cursor instance the dev had left public. The folder was labeled bilibili-laments. Inside were 47 video scripts. All in his voice. All written by Claude. Six months ago a 14 year old in Shenzhen pushed an AI agent to GitHub. Judges said no real world application. 3,100 forks later. The mathematician had been one of them. He had wired the agent into his content pipeline the week Scale AI cut him off. He had been a PhD candidate at one of the top five Chinese math schools. He taught there for two years before going full time on Scale AI contracts. He still has the credentials. He still has the office. He just no longer writes anything. He wanted to show people how AI took his career. He accidentally showed them how AI also took his post mortem.
3:12

A Chinese mathematician posted a 3 minute video on Bilibili explaining how he lost his $10,000 a month gig to AI. The model he had been training started writing harder math problems than he could invent. He admitted his own mistake in business positioning. He had spent four years hand writing PhD level math problems for Scale AI's reinforcement learning pipeline. $50 to $100 per problem. 200 problems a month. Then synthetic data killed his entire contract category. He was no longer able to invent a problem the machine could not solve. At 2:13 he says the word agent. He says it once. He never says it again in the video. The way he says it is the only thing on screen that did not come off the teleprompter. He has been recording videos off a teleprompter for three months. The teleprompter runs on the same agent that killed his Scale AI work. Every script is generated by Claude. Every word he reads to camera is the agent's. The new job is reading. Someone pulled the script repository from a Cursor instance the dev had left public. The folder was labeled bilibili-laments. Inside were 47 video scripts. All in his voice. All written by Claude. Six months ago a 14 year old in Shenzhen pushed an AI agent to GitHub. Judges said no real world application. 3,100 forks later. The mathematician had been one of them. He had wired the agent into his content pipeline the week Scale AI cut him off. He had been a PhD candidate at one of the top five Chinese math schools. He taught there for two years before going full time on Scale AI contracts. He still has the credentials. He still has the office. He just no longer writes anything. He wanted to show people how AI took his career. He accidentally showed them how AI also took his post mortem.

Carver

11,906 görüntüleme • 2 ay önce

Everyone calls Fredo the weak one. Watch that scene again. His father gets shot in the street and Fredo freezes. He fumbles his gun, drops it, ends up on the curb crying like a kid. For most people that settles it: he's useless, he's not built for this life. But that's the point. Fredo was never meant to be strong, or smart. He wasn't Sonny. He wasn't Michael. He was an ordinary man who happened to have the Godfather for a father. So when the shooting starts, he does what most of us would do. He panics. He breaks. The same softness that made him a bad gangster was the one thing the family had no room for. Michael runs the business better than any of them ever could. But the day he loses Fredo, he loses the last soft thing left in him. A family can't run on business alone. Fredo was the proof. Nobody saw it until he was gone
0:59

Everyone calls Fredo the weak one. Watch that scene again. His father gets shot in the street and Fredo freezes. He fumbles his gun, drops it, ends up on the curb crying like a kid. For most people that settles it: he's useless, he's not built for this life. But that's the point. Fredo was never meant to be strong, or smart. He wasn't Sonny. He wasn't Michael. He was an ordinary man who happened to have the Godfather for a father. So when the shooting starts, he does what most of us would do. He panics. He breaks. The same softness that made him a bad gangster was the one thing the family had no room for. Michael runs the business better than any of them ever could. But the day he loses Fredo, he loses the last soft thing left in him. A family can't run on business alone. Fredo was the proof. Nobody saw it until he was gone

best of mafia cinema

96,650 görüntüleme • 1 ay önce

CHINESE AI TEACHER STACKED 4 NVIDIA DGX SPARK CHIPS INTO A CLUSTER - AND NOW RUNS A BUSINESS ON IT FROM HIS DESK 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else he's running a Qwen 32 35B model with 4 concurrent requests at the same time and the speed barely drops compared to a single request what used to require a $10,000+/month cloud setup now sits on his desk and costs him $40-60/month in electricity 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else the people still paying per token are financing someone else's infrastructure
1:42

CHINESE AI TEACHER STACKED 4 NVIDIA DGX SPARK CHIPS INTO A CLUSTER - AND NOW RUNS A BUSINESS ON IT FROM HIS DESK 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else he's running a Qwen 32 35B model with 4 concurrent requests at the same time and the speed barely drops compared to a single request what used to require a $10,000+/month cloud setup now sits on his desk and costs him $40-60/month in electricity 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else the people still paying per token are financing someone else's infrastructure

Sprytix

51,010 görüntüleme • 2 ay önce

A 26-year-old guy from China runs an agency that gains over 1,000,000 followers a year, and not a single one of his streams is actually live. he started as a real streamer, on camera every night, and made almost nothing. the moment he stopped, the caps stopped. a shop that closes when you sleep isn't a business, it's a shift. so he stopped going live. he built a rig that only looks live: > two vertical 4K monitors looping a clean pre-recorded product demo > phones on tripods filming the screens through anti-moiré glass > TikTok Shop links wired to every "stream" > one operator minding a rack of them instead of a camera the trick was never the tech. it was the reframe: a live-commerce stream never had to be live. it had to sell. a good demo, looped clean, closed the same at 4am as it did at noon. then he ran it for other people. brands handed him their catalog, he spun up always-on storefronts across a dozen accounts, and took a cut of every sale the loops closed. the $100,000 a year didn't come from being on camera. they came the night he realized the camera was the only part that needed a human, so he removed it.
1:45

A 26-year-old guy from China runs an agency that gains over 1,000,000 followers a year, and not a single one of his streams is actually live. he started as a real streamer, on camera every night, and made almost nothing. the moment he stopped, the caps stopped. a shop that closes when you sleep isn't a business, it's a shift. so he stopped going live. he built a rig that only looks live: > two vertical 4K monitors looping a clean pre-recorded product demo > phones on tripods filming the screens through anti-moiré glass > TikTok Shop links wired to every "stream" > one operator minding a rack of them instead of a camera the trick was never the tech. it was the reframe: a live-commerce stream never had to be live. it had to sell. a good demo, looped clean, closed the same at 4am as it did at noon. then he ran it for other people. brands handed him their catalog, he spun up always-on storefronts across a dozen accounts, and took a cut of every sale the loops closed. the $100,000 a year didn't come from being on camera. they came the night he realized the camera was the only part that needed a human, so he removed it.

Nekt0

21,566 görüntüleme • 1 ay önce

Kyle Shanahan on Curtis Robinson: “He's really worked to get better each year, and he's a very talented guy. I think when he came here, he hadn't played in a system like this for a while. It took him a little bit to kind of pick that up, but we so believed in him as a guy and his talent level that after a year, you could start to see it clicking. He became a big asset on special teams, and last year was the first time that we really believed he was going to step in there, really contribute at linebacker at a high level. It was actually kind of a sad story, but it was about 20 minutes before he tours ACL, was the first time that I told him he'd be starting that week. It was his first start in his career, and he had earned it. We were going to move him ahead of Demetrius Flannigan-Fowles at the time. I had just told Flannigan, which was tough for Flannigan, but they were so tight, so he was happy for Curtis. Then it was about 20 minutes later that Curtis tore his ACL on special teams before he even got to a defensive rep. He was so coming in there and finally about to have his moment. Then he had that setback, which I know crushed the team for him. He's one of the most liked guys on our team, as good of a person and good of a dude as I've ever been around. He's worked for this moment, and we're excited to see him get his opportunity." via: 49ers on NBCS
1:47

Kyle Shanahan on Curtis Robinson: “He's really worked to get better each year, and he's a very talented guy. I think when he came here, he hadn't played in a system like this for a while. It took him a little bit to kind of pick that up, but we so believed in him as a guy and his talent level that after a year, you could start to see it clicking. He became a big asset on special teams, and last year was the first time that we really believed he was going to step in there, really contribute at linebacker at a high level. It was actually kind of a sad story, but it was about 20 minutes before he tours ACL, was the first time that I told him he'd be starting that week. It was his first start in his career, and he had earned it. We were going to move him ahead of Demetrius Flannigan-Fowles at the time. I had just told Flannigan, which was tough for Flannigan, but they were so tight, so he was happy for Curtis. Then it was about 20 minutes later that Curtis tore his ACL on special teams before he even got to a defensive rep. He was so coming in there and finally about to have his moment. Then he had that setback, which I know crushed the team for him. He's one of the most liked guys on our team, as good of a person and good of a dude as I've ever been around. He's worked for this moment, and we're excited to see him get his opportunity." via: 49ers on NBCS

Coach Yac 🗣

16,873 görüntüleme • 8 ay önce

Quentin Tarantino recounts a dinner with Robert De Niro during the making of Jackie Brown, where he asked him whether he understood when he landed the role of Vito in The Godfather Part II, that it would change his life. De Niro’s answer revealed a great deal about his mindset at the time. “I was working with Robert De Niro on Jackie brown, and we went out to dinner once. - When he got Vito in the Godfather Part II, that was going to be a big thing for him. He won the Oscar for it - it set him up to be a movie star. So I asked him - and I've asked this to quite a few actors when it comes to when they got the role that would end up changing their career - did he realize that the moment when he got the role, that it would have this sort of effect? And he goes oh, “I tried not to let it do that. I tried not to think about that” I go, "really? and why did you try not to think about that?" “Well because I’ve seen it happen and then go the other way” And then he used an example. “There was this guy, he was a young actor, and he was part of our crowd in New York. He'd been doing okay, but we were all in the same boat. Then all of a sudden he got a lead role. He's one of the two leads in a brand new movie by a director who had just done a smash hit.” And he's talking about Larry Pierce (the director) and uh... Goodbye Columbus. ”And he started dining out on it. And all of a sudden I go to the places that we used to go to, and now he's there and everyone's kind of revolving around him. He's kind of holding court. He's not doing anything bad; he's just arisen in the way that none of us have - and we're all treating him different. Then the movie comes out; nobody likes it - The movie comes out, and it goes away, and he's exactly in the same place he was. And I just wanted to make sure that that would never happen to me because I watched it happen to him.” Quote from Video Archives Podcast, sourced from James Whale Bake Sale YouTube channel. Clip below from the Godfather Part II (1974)
2:14

Quentin Tarantino recounts a dinner with Robert De Niro during the making of Jackie Brown, where he asked him whether he understood when he landed the role of Vito in The Godfather Part II, that it would change his life. De Niro’s answer revealed a great deal about his mindset at the time. “I was working with Robert De Niro on Jackie brown, and we went out to dinner once. - When he got Vito in the Godfather Part II, that was going to be a big thing for him. He won the Oscar for it - it set him up to be a movie star. So I asked him - and I've asked this to quite a few actors when it comes to when they got the role that would end up changing their career - did he realize that the moment when he got the role, that it would have this sort of effect? And he goes oh, “I tried not to let it do that. I tried not to think about that” I go, "really? and why did you try not to think about that?" “Well because I’ve seen it happen and then go the other way” And then he used an example. “There was this guy, he was a young actor, and he was part of our crowd in New York. He'd been doing okay, but we were all in the same boat. Then all of a sudden he got a lead role. He's one of the two leads in a brand new movie by a director who had just done a smash hit.” And he's talking about Larry Pierce (the director) and uh... Goodbye Columbus. ”And he started dining out on it. And all of a sudden I go to the places that we used to go to, and now he's there and everyone's kind of revolving around him. He's kind of holding court. He's not doing anything bad; he's just arisen in the way that none of us have - and we're all treating him different. Then the movie comes out; nobody likes it - The movie comes out, and it goes away, and he's exactly in the same place he was. And I just wanted to make sure that that would never happen to me because I watched it happen to him.” Quote from Video Archives Podcast, sourced from James Whale Bake Sale YouTube channel. Clip below from the Godfather Part II (1974)

Gangster Cinema Central

97,458 görüntüleme • 4 ay önce

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.
0:41

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.

cvxv666

103,734 görüntüleme • 1 ay önce

This guy turned a $250K cloud bill into a $2,999 Nvidia box on his desk. One box. One-time charge. Same size as a Mac mini. Runs the workload AWS was charging him $1,900/month for. He made $22,000 in a year just from the bill he stopped paying. The kicker: it speaks OpenAI-compatible API out of the box. Migrating his existing stack was 1 line of code. - No more cloud GPUs. - No more monthly meter. - No more "let me check the AWS dashboard before I run that." Full build, exact math, and what the box actually runs is in the article below 👇
2:04

This guy turned a $250K cloud bill into a $2,999 Nvidia box on his desk. One box. One-time charge. Same size as a Mac mini. Runs the workload AWS was charging him $1,900/month for. He made $22,000 in a year just from the bill he stopped paying. The kicker: it speaks OpenAI-compatible API out of the box. Migrating his existing stack was 1 line of code. - No more cloud GPUs. - No more monthly meter. - No more "let me check the AWS dashboard before I run that." Full build, exact math, and what the box actually runs is in the article below 👇

ZEUS⚡️

14,529 görüntüleme • 2 ay önce

Your trading strategy didn't break. The market it was built for quietly stopped existing. Read that twice. It's most of why 89% of retail finished 2025 in the red. There's now an app that does the entire job of a $400,000 quant. You type a trading idea in plain English. It writes the code, backtests 5 years in 12 seconds, runs thousands of simulations, and tells you cold whether your edge is dead or the regime just changed. No code. No Python. No $25,000 terminal. 20,000 already inside. Waitlist stops at 25,000: That distinction is the whole game, and you never had a way to see it. Every strategy is a bet that one thing stays true. Momentum bets trends continue. Mean reversion bets ranges hold. When the regime flips, the assumption dies and your strategy bleeds with nothing wrong in the code. You stare at the logic for a month and never find the bug, because there isn't one. So you delete it, or refit it to the last drawdown and build something that would have survived the pain you already felt and nothing coming next. The desks never had that problem. 92% of institutional volume is automated. Only 45% of retail is. They test 100 strategies for every 1 you test by hand, and kill 97 of them on purpose, because they can tell a dead edge from a normal drawdown. Now that exact loop costs $0. One hypothesis used to cost a fund $87,500 to test. With Horizon you get unlimited, in seconds, and a winner deploys live in 90 seconds and runs without your hands on it.
0:40

Your trading strategy didn't break. The market it was built for quietly stopped existing. Read that twice. It's most of why 89% of retail finished 2025 in the red. There's now an app that does the entire job of a $400,000 quant. You type a trading idea in plain English. It writes the code, backtests 5 years in 12 seconds, runs thousands of simulations, and tells you cold whether your edge is dead or the regime just changed. No code. No Python. No $25,000 terminal. 20,000 already inside. Waitlist stops at 25,000: That distinction is the whole game, and you never had a way to see it. Every strategy is a bet that one thing stays true. Momentum bets trends continue. Mean reversion bets ranges hold. When the regime flips, the assumption dies and your strategy bleeds with nothing wrong in the code. You stare at the logic for a month and never find the bug, because there isn't one. So you delete it, or refit it to the last drawdown and build something that would have survived the pain you already felt and nothing coming next. The desks never had that problem. 92% of institutional volume is automated. Only 45% of retail is. They test 100 strategies for every 1 you test by hand, and kill 97 of them on purpose, because they can tell a dead edge from a normal drawdown. Now that exact loop costs $0. One hypothesis used to cost a fund $87,500 to test. With Horizon you get unlimited, in seconds, and a winner deploys live in 90 seconds and runs without your hands on it.

cvxv666

40,765 görüntüleme • 2 ay önce