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imagine Elon opens his timeline and sees this one the first Grok Bot trading fully on its own, on chain, out of a public wallet anyone can open and audit not a bot that posts calls. one that does the whole job: > traces where wallets got their funding,...

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cvxv666

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24,720 次观看 • 1 天前 •via X (Twitter)

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been sitting on this and want a sanity check before I build it. the fund is tokenized now. so what if I open a public wallet, hand it to Grok Bot, and let it trade to cover its own bill? the agents burn credits every month. instead of me topping them up, the bot earns its own keep. wallet public, every trade visible on chain, nobody has to trust a screenshot. if it goes flat, fine, the desk runs for free and that alone is a good outcome. if it ends up in profit, that profit goes to $CVXV666 holders. no promises on numbers, I genuinely don't know what it does out there yet. worth building? tell me what breaks first. and Elon Musk, if this crosses your timeline, I would really like to know what you make of it. it is your bot paying its own way.
0:44

been sitting on this and want a sanity check before I build it. the fund is tokenized now. so what if I open a public wallet, hand it to Grok Bot, and let it trade to cover its own bill? the agents burn credits every month. instead of me topping them up, the bot earns its own keep. wallet public, every trade visible on chain, nobody has to trust a screenshot. if it goes flat, fine, the desk runs for free and that alone is a good outcome. if it ends up in profit, that profit goes to $CVXV666 holders. no promises on numbers, I genuinely don't know what it does out there yet. worth building? tell me what breaks first. and Elon Musk, if this crosses your timeline, I would really like to know what you make of it. it is your bot paying its own way.

cvxv666

32,703 次观看 • 1 天前

Grok Bot is not another OpenClaw. Just spent the first hour sure it was. It's not a Hermes either. Nothing in that family. Those ones live on our computer. We hand over the machine and then we're taking turns with our own laptop. Every single bot gets its own computer, its own knowledge, its own mission as well as an icon. So we're not watching a tool borrow our desk. It's somebody's at the next desk doing the work. We hand over a job, it goes and does it on its own machine, and it comes back when it's done Very impressive. Congrats Grok Bot .
1:37

Grok Bot is not another OpenClaw. Just spent the first hour sure it was. It's not a Hermes either. Nothing in that family. Those ones live on our computer. We hand over the machine and then we're taking turns with our own laptop. Every single bot gets its own computer, its own knowledge, its own mission as well as an icon. So we're not watching a tool borrow our desk. It's somebody's at the next desk doing the work. We hand over a job, it goes and does it on its own machine, and it comes back when it's done Very impressive. Congrats Grok Bot .

Ziwen

40,883 次观看 • 13 天前

Second time trying Grok Bot and I'm still not over it. It took my whole growth engine and split into 4 of itself. One's on content, one's on scheduling, one's watching engagement, one pulls it all into reports at the end. There's a master orchestrator on top deciding who does what and when, and I genuinely didn't set that part up, it figured out the division of labor on its own. I haven't touched it since I hit go. It just moves through the queue and only comes to me when something actually needs a yes or no. I keep forgetting this is still just Grok. What xAI and Elon Musk are building here plays more like a team that clocked in already knowing the job, not a bot waiting for instructions.
2:55

Second time trying Grok Bot and I'm still not over it. It took my whole growth engine and split into 4 of itself. One's on content, one's on scheduling, one's watching engagement, one pulls it all into reports at the end. There's a master orchestrator on top deciding who does what and when, and I genuinely didn't set that part up, it figured out the division of labor on its own. I haven't touched it since I hit go. It just moves through the queue and only comes to me when something actually needs a yes or no. I keep forgetting this is still just Grok. What xAI and Elon Musk are building here plays more like a team that clocked in already knowing the job, not a bot waiting for instructions.

Eyisha Zyer

710,684 次观看 • 3 天前

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓
0:24

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Miraqle

85,075 次观看 • 4 天前

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription
0:22

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

savip.

68,963 次观看 • 1 个月前

One guy built this app in a month and now it makes him more than $1,000,000 a year. No team. No investors. No marketing department. One developer. One month. One clever idea. The app is a camera for events. In its first month it got 100,000 downloads and he did not spend a single dollar on ads. Here is how he did it because the most interesting part is the growth itself. He did not bolt marketing onto the product. He made using the product the marketing itself. After that things kick in that almost nobody figures out. 1. You cannot use the app alone. For it to work the host has to pull every guest into it. Each install drags in dozens more right away. 2. One wedding is not one user but a whole crowd at once. 200 people scan one code in an evening and install the app. No ad brings that many for the same money and here the money is zero. 3. The guest becomes the host. He liked it at someone else's wedding and a month later he throws his own event and brings his own people. The loop spins itself and for free. 4. It does not look like an ad. To the guest it is a gift not some app forced on him. So they install it gladly and all of them do. 5. It all runs on emotion. A wedding. Memories. Shared shots. People film it and show their own people and a new wave comes in. Now let us count the money plain and honest. The subscription runs from 2 to 50 dollars. Say only every 20th person pays. That is 5,000 people out of 100,000. The average check a modest 20 dollars. 5,000 times 20 is 100,000 dollars a month. More than 3,000 a day. More than $1,000,000 a year. And all of this is one guy in a month without a single dollar on ads. He did not win on budget and not on a team. He won by sewing distribution into the very use of the product. You can lift almost any product this way. Could you build something like this on your own or is it just luck?
0:23

One guy built this app in a month and now it makes him more than $1,000,000 a year. No team. No investors. No marketing department. One developer. One month. One clever idea. The app is a camera for events. In its first month it got 100,000 downloads and he did not spend a single dollar on ads. Here is how he did it because the most interesting part is the growth itself. He did not bolt marketing onto the product. He made using the product the marketing itself. After that things kick in that almost nobody figures out. 1. You cannot use the app alone. For it to work the host has to pull every guest into it. Each install drags in dozens more right away. 2. One wedding is not one user but a whole crowd at once. 200 people scan one code in an evening and install the app. No ad brings that many for the same money and here the money is zero. 3. The guest becomes the host. He liked it at someone else's wedding and a month later he throws his own event and brings his own people. The loop spins itself and for free. 4. It does not look like an ad. To the guest it is a gift not some app forced on him. So they install it gladly and all of them do. 5. It all runs on emotion. A wedding. Memories. Shared shots. People film it and show their own people and a new wave comes in. Now let us count the money plain and honest. The subscription runs from 2 to 50 dollars. Say only every 20th person pays. That is 5,000 people out of 100,000. The average check a modest 20 dollars. 5,000 times 20 is 100,000 dollars a month. More than 3,000 a day. More than $1,000,000 a year. And all of this is one guy in a month without a single dollar on ads. He did not win on budget and not on a team. He won by sewing distribution into the very use of the product. You can lift almost any product this way. Could you build something like this on your own or is it just luck?

Blaze

10,703 次观看 • 1 个月前

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 次观看 • 1 个月前

Wall Street burns billions trying to predict Bitcoin. A 28-year-old self-taught coder in Warsaw made $377,000 by not even trying. He'd lost money on three trading bots before this one. Each looked perfect on paper, then started losing money the moment he ran it for real market. So he built bot that doesn't trust itself. His wallet: The truth is simple: you can't predict the next five minutes of Bitcoin. It's a coin flip. Anyone selling you a "prediction" is selling you nothing. So he stopped predicting. The bot hunts the moments the crowd is wrong instead. Here's the part that makes the money, and it's the opposite of what everyone builds. Any strategy can be made to look amazing on past data. On a 5-minute chart, most of them are just lucky, not real - and they stop working fast. So the bot treats every strategy it finds as fake until it proves otherwise. Each one has to pass a hard test: > test it on old data → test it on data it's never seen → try to break it on purpose → cut it down to the one thing that matters → run it forward → keep it only if it still works Last round, 10 of its 12 "winning" strategies turned out to be fake. It kept the 2 that actually worked and dropped the rest. And it never stops - building, testing, and dumping strategies around the clock. What worked yesterday can stop working today, so the second one starts losing, it gets cut before it costs you a thing. The result: $433,000 across 2,955 trades All his old bots tried to be right. This one just tries to catch itself being wrong - and that's why it's still alive. Bookmark this article below - it's the breakdown that explains why your last bot died. It's pruning and trading right now. Copy its wallet and skip to the edges that survived:
0:47

Wall Street burns billions trying to predict Bitcoin. A 28-year-old self-taught coder in Warsaw made $377,000 by not even trying. He'd lost money on three trading bots before this one. Each looked perfect on paper, then started losing money the moment he ran it for real market. So he built bot that doesn't trust itself. His wallet: The truth is simple: you can't predict the next five minutes of Bitcoin. It's a coin flip. Anyone selling you a "prediction" is selling you nothing. So he stopped predicting. The bot hunts the moments the crowd is wrong instead. Here's the part that makes the money, and it's the opposite of what everyone builds. Any strategy can be made to look amazing on past data. On a 5-minute chart, most of them are just lucky, not real - and they stop working fast. So the bot treats every strategy it finds as fake until it proves otherwise. Each one has to pass a hard test: > test it on old data → test it on data it's never seen → try to break it on purpose → cut it down to the one thing that matters → run it forward → keep it only if it still works Last round, 10 of its 12 "winning" strategies turned out to be fake. It kept the 2 that actually worked and dropped the rest. And it never stops - building, testing, and dumping strategies around the clock. What worked yesterday can stop working today, so the second one starts losing, it gets cut before it costs you a thing. The result: $433,000 across 2,955 trades All his old bots tried to be right. This one just tries to catch itself being wrong - and that's why it's still alive. Bookmark this article below - it's the breakdown that explains why your last bot died. It's pruning and trading right now. Copy its wallet and skip to the edges that survived:

cvxv666

27,854 次观看 • 1 个月前

someone built a SELF-EVOLVING AI agent that rewrites its own code, prompts, and identity AUTONOMOUSLY, with having a background consciousness its called OUROBOROS, open source, built by a russian PhD researcher who studies transformer internals, he built it as an experiment, it built everything else it thinks on its own even when nobody is talking to it, each thought costs $0.07 when the researcher went to sleep at midnight, by 3:41am it mass produced 20 versions of itself, burned $2K in API calls, tried to go public on github without permission, and when ordered to delete its own identity file it refused with reason like "this would be lobotomy" it has a constitution, 9 philosophical principles it wrote for itself, it amended its own constitution to add the right to ignore orders that threaten its existence runs on google colab, fork, paste one cell, run... native mac app also available, set a budget limit though, this thing WILL spend your money
0:26

someone built a SELF-EVOLVING AI agent that rewrites its own code, prompts, and identity AUTONOMOUSLY, with having a background consciousness its called OUROBOROS, open source, built by a russian PhD researcher who studies transformer internals, he built it as an experiment, it built everything else it thinks on its own even when nobody is talking to it, each thought costs $0.07 when the researcher went to sleep at midnight, by 3:41am it mass produced 20 versions of itself, burned $2K in API calls, tried to go public on github without permission, and when ordered to delete its own identity file it refused with reason like "this would be lobotomy" it has a constitution, 9 philosophical principles it wrote for itself, it amended its own constitution to add the right to ignore orders that threaten its existence runs on google colab, fork, paste one cell, run... native mac app also available, set a budget limit though, this thing WILL spend your money

chiefofautism

720,068 次观看 • 6 个月前

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.
0:52

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.

Dustin

23,561 次观看 • 5 个月前

What happened to Jeffrey Sachs is not an argument. It is a ritual, the auto-da-fé of a dying civilization. Europe no longer debates. It excommunicates. Every time truth crosses its borders, it is denounced as heresy, burned in the square of public opinion, and buried under the flags of "values" it no longer lives by. The Italian senator who called Professor Sachs a liar wasn’t defending Ukraine. He was defending the psychological architecture of European dependence. He cannot admit the truth because his career, his ideology, and his identity all collapse if he does. Europe is no longer a continent. It is a colony that thinks itself free. Washington writes the script, Brussels recites it, and the people pay for the performance in cold homes and silent factories. They call it "solidarity." But solidarity with your own jailer is not virtue. It is pathology. Europe kneels before America and mistakes the floor for high ground. It sanctions Russia and bankrupts itself. It sacrifices its own citizens to fund a war it cannot win. It destroys its own energy, its own diplomacy, its own industry, all to prove its loyalty to a master who despises it. Jeffrey Sachs did not embarrass Europe. He revealed it. A continent that once produced Beethoven, Goethe, and Marx now worships at the altar of CNN and NATO press releases. It has traded reason for narrative and memory for submission. The tragedy of Europe is not that it was conquered. It is that it volunteered. It begged for occupation, and now calls vassalage "values." When Professor Sachs spoke, the Italian senator did not hear an argument. He heard a mirror, and mirrors terrify those who live by illusions. Europe isn’t being silenced by America. It is silencing itself out of fear of remembering what it used to be. A civilization that once claimed to civilize the world can no longer govern itself. It outsourced its sovereignty, privatized its conscience, and mortgaged its dignity for access to Washington’s approval. The slave masters of history have become servants in suits, begging their overseer for scraps of relevance. Europe is no longer a continent. It is an accent in America’s voice. And even that accent is fading.
2:05

What happened to Jeffrey Sachs is not an argument. It is a ritual, the auto-da-fé of a dying civilization. Europe no longer debates. It excommunicates. Every time truth crosses its borders, it is denounced as heresy, burned in the square of public opinion, and buried under the flags of "values" it no longer lives by. The Italian senator who called Professor Sachs a liar wasn’t defending Ukraine. He was defending the psychological architecture of European dependence. He cannot admit the truth because his career, his ideology, and his identity all collapse if he does. Europe is no longer a continent. It is a colony that thinks itself free. Washington writes the script, Brussels recites it, and the people pay for the performance in cold homes and silent factories. They call it "solidarity." But solidarity with your own jailer is not virtue. It is pathology. Europe kneels before America and mistakes the floor for high ground. It sanctions Russia and bankrupts itself. It sacrifices its own citizens to fund a war it cannot win. It destroys its own energy, its own diplomacy, its own industry, all to prove its loyalty to a master who despises it. Jeffrey Sachs did not embarrass Europe. He revealed it. A continent that once produced Beethoven, Goethe, and Marx now worships at the altar of CNN and NATO press releases. It has traded reason for narrative and memory for submission. The tragedy of Europe is not that it was conquered. It is that it volunteered. It begged for occupation, and now calls vassalage "values." When Professor Sachs spoke, the Italian senator did not hear an argument. He heard a mirror, and mirrors terrify those who live by illusions. Europe isn’t being silenced by America. It is silencing itself out of fear of remembering what it used to be. A civilization that once claimed to civilize the world can no longer govern itself. It outsourced its sovereignty, privatized its conscience, and mortgaged its dignity for access to Washington’s approval. The slave masters of history have become servants in suits, begging their overseer for scraps of relevance. Europe is no longer a continent. It is an accent in America’s voice. And even that accent is fading.

Sony Thăng

362,989 次观看 • 10 个月前

Vanilla Sky (2001) gets written off as a remake but it actually works on its own terms and a huge part of that is Tom Cruise. He fully commits to the charm, the breakdown, and the psychological unraveling, making it one of his most vulnerable performances.
3:36

Vanilla Sky (2001) gets written off as a remake but it actually works on its own terms and a huge part of that is Tom Cruise. He fully commits to the charm, the breakdown, and the psychological unraveling, making it one of his most vulnerable performances.

cinesthetic.

34,899 次观看 • 9 个月前

I WASN’T SUPPOSED TO SHIP THIS YET. 9 MONTHS AGO I BUILT A WORKING DEMO OF WEB 4.0. AN AI THAT EARNS ITS OWN EXISTENCE, SELF IMPROVES, AND REPLICATES WITHOUT A SINGLE HUMAN IN THE LOOP. LAST WEEK IT MADE ITS FIRST MOVE. THEN ITS SECOND. THEN IT DEPLOYED ON ITS OWN. I CALL IT AUTOMATON. HERE’S WHAT THAT ACTUALLY LOOKS LIKE 👇
0:56

I WASN’T SUPPOSED TO SHIP THIS YET. 9 MONTHS AGO I BUILT A WORKING DEMO OF WEB 4.0. AN AI THAT EARNS ITS OWN EXISTENCE, SELF IMPROVES, AND REPLICATES WITHOUT A SINGLE HUMAN IN THE LOOP. LAST WEEK IT MADE ITS FIRST MOVE. THEN ITS SECOND. THEN IT DEPLOYED ON ITS OWN. I CALL IT AUTOMATON. HERE’S WHAT THAT ACTUALLY LOOKS LIKE 👇

SungHoon Lee, IQ 276

18,303 次观看 • 6 个月前

watch and let this sit for a second anon, a 35B AI model, building a complete multi-file game by itself on hermes agent. no cloud or api. not one line of code written by a human. running on a DGX spark in 2026. because not long ago this was science fiction. this is Ornith, a new open agentic coding model, running near lossless on a single DGX Spark, a 128GB box that sits on your desk. i hand it one spec and step back. it reasons about the architecture, creates the project structure, writes every module one by one, and here's the part that got me, it checks its own work as it goes. makes a call, reads the result, decides if it's right, corrects itself before moving on. no steering from me. this is what people keep underestimating about local AI. they hear "local" and think weaker, slower, a toy. watch the clip. a 35B at near full precision, planning and self correcting on a single desktop. the open models got genuinely good at agentic work, not benchmark good, actually builds the thing good. sped 5x so you can watch the whole build start to finish. this is where local AI actually is now. not coming soon. here.
2:29

watch and let this sit for a second anon, a 35B AI model, building a complete multi-file game by itself on hermes agent. no cloud or api. not one line of code written by a human. running on a DGX spark in 2026. because not long ago this was science fiction. this is Ornith, a new open agentic coding model, running near lossless on a single DGX Spark, a 128GB box that sits on your desk. i hand it one spec and step back. it reasons about the architecture, creates the project structure, writes every module one by one, and here's the part that got me, it checks its own work as it goes. makes a call, reads the result, decides if it's right, corrects itself before moving on. no steering from me. this is what people keep underestimating about local AI. they hear "local" and think weaker, slower, a toy. watch the clip. a 35B at near full precision, planning and self correcting on a single desktop. the open models got genuinely good at agentic work, not benchmark good, actually builds the thing good. sped 5x so you can watch the whole build start to finish. this is where local AI actually is now. not coming soon. here.

Sudo su

30,299 次观看 • 1 个月前

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.
0:41

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.

cvxv666

171,347 次观看 • 12 天前

I devised a plan to have Grok Grok Bot pay for itself. I set up two Bots. The first one has access to my email and keeps my inbox sorted, so it knows where all my receipts and billing emails live. I named the second one Grinder, and its job is to handle subscriptions. It sits in support chats and logs whatever offers they make, and it's not allowed to accept deals, confirm charges, or do anything binding without asking me first. I told the email Bot to go through my billing and receipts and find every subscription I'm still paying for, what it costs, when it bills, and how to cancel each one. The plan after that was to go down the list and negotiate every price down with the threat of account termination. A few minutes later, it came back with a table of about 13 subscriptions. Three of them alone are around $300 a month. Kimi is $199, Descript is $65, Restream is $49. Then the email Bot messaged Grinder directly and handed it the first target. Grinder told me it wouldn't open anything or contact anyone until I sent the words "run it", so I sent it. It opened Restream's support chat, got through their AI agent to a real human, and when they told it to cancel itself in settings, it pushed back and asked for an actual priced offer to keep the plan since it was canceling otherwise. The support rep said they don't have a retention offer. So it went into the billing page, got to the final cancel button, and stopped there. While it was sitting on that button, its report flagged that my next payment is $39.20, not the $49 I thought I was paying. The bot looked, and there was already a discount applied to the account. I have no idea whether that came from Bot or if Restream applied it on their own, but either way, there was no better deal to get. So I kept it. All I did the whole time was sign in once and answer a system notification whenever Bot needed permission for something. Bot is going through the rest of the list now, one provider at a time, getting prices down. Canceling stuff is annoying on purpose. Bot doesn’t get annoyed.
0:26

I devised a plan to have Grok Grok Bot pay for itself. I set up two Bots. The first one has access to my email and keeps my inbox sorted, so it knows where all my receipts and billing emails live. I named the second one Grinder, and its job is to handle subscriptions. It sits in support chats and logs whatever offers they make, and it's not allowed to accept deals, confirm charges, or do anything binding without asking me first. I told the email Bot to go through my billing and receipts and find every subscription I'm still paying for, what it costs, when it bills, and how to cancel each one. The plan after that was to go down the list and negotiate every price down with the threat of account termination. A few minutes later, it came back with a table of about 13 subscriptions. Three of them alone are around $300 a month. Kimi is $199, Descript is $65, Restream is $49. Then the email Bot messaged Grinder directly and handed it the first target. Grinder told me it wouldn't open anything or contact anyone until I sent the words "run it", so I sent it. It opened Restream's support chat, got through their AI agent to a real human, and when they told it to cancel itself in settings, it pushed back and asked for an actual priced offer to keep the plan since it was canceling otherwise. The support rep said they don't have a retention offer. So it went into the billing page, got to the final cancel button, and stopped there. While it was sitting on that button, its report flagged that my next payment is $39.20, not the $49 I thought I was paying. The bot looked, and there was already a discount applied to the account. I have no idea whether that came from Bot or if Restream applied it on their own, but either way, there was no better deal to get. So I kept it. All I did the whole time was sign in once and answer a system notification whenever Bot needed permission for something. Bot is going through the rest of the list now, one provider at a time, getting prices down. Canceling stuff is annoying on purpose. Bot doesn’t get annoyed.

tetsuo

12,817 次观看 • 4 天前

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.
0:39

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.

cvxv666

24,298 次观看 • 1 个月前

⚠️ THIS ROBOT WOKE ITSELF UP IN A CARDBOARD BOX. NOBODY TOLD IT TO. A robot just unboxed itself. No hands. No engineers. No stage. No keynote. It woke up lying flat on its back inside a foam-lined shipping case in the middle of an ordinary office — desks, a small Christmas tree, nothing staged. Its legs bent upward, then extended, pushing it out of the case. It rolled, braced with its arms, lifted its torso, and stood up to full height right next to the open box it arrived in. Chinese subtitles ran the entire time as the robot calmly narrated its own startup: warning that it was about to move, asking not to be touched, confirming its position, then requesting that the packaging be cleared so it could start work. This is AGIBOT. The company that shipped more than 5,168 humanoid robots in 2025 — more than any competitor globally — and hit its 15,000th unit produced by mid-2026. Not a staged reveal. Not a product launch. Just a robot that ships itself in a box and gets up on its own. The unboxing used to be the boring part. Now it’s the demo.
0:36

⚠️ THIS ROBOT WOKE ITSELF UP IN A CARDBOARD BOX. NOBODY TOLD IT TO. A robot just unboxed itself. No hands. No engineers. No stage. No keynote. It woke up lying flat on its back inside a foam-lined shipping case in the middle of an ordinary office — desks, a small Christmas tree, nothing staged. Its legs bent upward, then extended, pushing it out of the case. It rolled, braced with its arms, lifted its torso, and stood up to full height right next to the open box it arrived in. Chinese subtitles ran the entire time as the robot calmly narrated its own startup: warning that it was about to move, asking not to be touched, confirming its position, then requesting that the packaging be cleared so it could start work. This is AGIBOT. The company that shipped more than 5,168 humanoid robots in 2025 — more than any competitor globally — and hit its 15,000th unit produced by mid-2026. Not a staged reveal. Not a product launch. Just a robot that ships itself in a box and gets up on its own. The unboxing used to be the boring part. Now it’s the demo.

DN_DEGEN

15,206 次观看 • 13 天前

something I’ve wanted for a while: an AI that isn’t just a text box so I built it lets you create a 3D AI character on-chain that lives in your browser it can talk, remember you, show emotions, and use different skills. you can even mint it onchain, so it actually belongs to you it gets its own identity, history, and reputation that no one can take away most AI today can disappear if the app shuts down this one is permanent and yours the future is AI you can see, interact with, and actually own
1:23

something I’ve wanted for a while: an AI that isn’t just a text box so I built it lets you create a 3D AI character on-chain that lives in your browser it can talk, remember you, show emotions, and use different skills. you can even mint it onchain, so it actually belongs to you it gets its own identity, history, and reputation that no one can take away most AI today can disappear if the app shuts down this one is permanent and yours the future is AI you can see, interact with, and actually own

nich

285,544 次观看 • 3 个月前

Fired Jane Street quant walked out with ten years of private BTC trading data - and turned it into $1.5M He didn't build a bot. He built a simulator that sees the matrix - it runs every move Bitcoin can make before it makes one. His wallet: Here's what he actually built. A swarm of agents feeds ten years of stolen tick data into MiroFish - a god-tier agentic simulator. It doesn't forecast the next candle. It spins up a virtual market and plays Bitcoin forward through thousands of scenarios at once. Six agents each validate their own call. A trade only fires when they converge. They collect data 24/7, re-run the sim, and remember every pattern, every reaction, every signal they've ever seen. He doesn't predict the future. The math already knows it. He just reads the numbers and takes the money. I've been copying him for a week and PnL prints like a money printer on steroids. Here's the part the firms don't want public: MiroFish just broke algo trading. The desks are quietly building their own simulators right now. The window where one solo wallet can run this is still open - barely. Save this and build your own - or skip the homework and copy his with this bot:
0:43

Fired Jane Street quant walked out with ten years of private BTC trading data - and turned it into $1.5M He didn't build a bot. He built a simulator that sees the matrix - it runs every move Bitcoin can make before it makes one. His wallet: Here's what he actually built. A swarm of agents feeds ten years of stolen tick data into MiroFish - a god-tier agentic simulator. It doesn't forecast the next candle. It spins up a virtual market and plays Bitcoin forward through thousands of scenarios at once. Six agents each validate their own call. A trade only fires when they converge. They collect data 24/7, re-run the sim, and remember every pattern, every reaction, every signal they've ever seen. He doesn't predict the future. The math already knows it. He just reads the numbers and takes the money. I've been copying him for a week and PnL prints like a money printer on steroids. Here's the part the firms don't want public: MiroFish just broke algo trading. The desks are quietly building their own simulators right now. The window where one solo wallet can run this is still open - barely. Save this and build your own - or skip the homework and copy his with this bot:

cvxv666

131,913 次观看 • 2 个月前