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This guy bought a $400 Mac mini and walked into a coffee shop with $2,100 for installing an AI agent that never touches the internet. I had to rewatch this because the pitch is almost too simple. He shows up, plugs in the Mac mini, installs a local AI...

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BrainRul

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4,700,896 views • 1 month ago •via X (Twitter)

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This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.
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This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.

Gipp 🦅

591,405 views • 3 months ago

A HARDWARE MODDER BOLTED A BATTERY PACK ONTO A $599 MAC MINI M4 AND TURNED A DESK SERVER INTO A BACKPACK AI RIG THAT RUNS FOR EIGHT HOURS WITHOUT A WALL OUTLET he posts a video of the mac mini with a slim battery module clamped to the side, USB-C plugged into the back. no power brick, no outlet, just the 10 to 30W draw of the M4 chip pulling from a 20,000mAh bank. a full work day on one charge. this is not a portable laptop trick. it is a desk-class AI server that fits in a sling bag the same $599 mac mini i recommended in last week's article as the silent default, now untethered. pair it with a mobile hotspot or a Starlink mini and you have a fully off-grid LLM stack that answers questions in a forest, on a plane, in a power outage. the model lives in the box, the battery powers the box, that is the whole stack this is not a gadget. it is the first time the words "AI server" and "fits in your bag" belong in the same sentence
0:19

A HARDWARE MODDER BOLTED A BATTERY PACK ONTO A $599 MAC MINI M4 AND TURNED A DESK SERVER INTO A BACKPACK AI RIG THAT RUNS FOR EIGHT HOURS WITHOUT A WALL OUTLET he posts a video of the mac mini with a slim battery module clamped to the side, USB-C plugged into the back. no power brick, no outlet, just the 10 to 30W draw of the M4 chip pulling from a 20,000mAh bank. a full work day on one charge. this is not a portable laptop trick. it is a desk-class AI server that fits in a sling bag the same $599 mac mini i recommended in last week's article as the silent default, now untethered. pair it with a mobile hotspot or a Starlink mini and you have a fully off-grid LLM stack that answers questions in a forest, on a plane, in a power outage. the model lives in the box, the battery powers the box, that is the whole stack this is not a gadget. it is the first time the words "AI server" and "fits in your bag" belong in the same sentence

shmidt

31,619 views • 2 months ago

This guy from China makes $12,500 a month walking around crypto conferences with a backpack and a Mac Mini inside it. The setup is a Mac Mini running OpenClaw on a CUKTECH 10 Mini battery. Every other creator at these events waits until they're back at the hotel to process and upload. By then the alpha is gone and the thread is late. His portable AI catches keynote audio on the spot, extracts what matters and posts while everyone else is still in the room listening.
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This guy from China makes $12,500 a month walking around crypto conferences with a backpack and a Mac Mini inside it. The setup is a Mac Mini running OpenClaw on a CUKTECH 10 Mini battery. Every other creator at these events waits until they're back at the hotel to process and upload. By then the alpha is gone and the thread is late. His portable AI catches keynote audio on the spot, extracts what matters and posts while everyone else is still in the room listening.

0xMarioNawfal

69,101 views • 2 months ago

MARCUS CHEN STACKED 30 MAC MINIS INTO AN AI SERVER FARM. ONE $599 MAC MINI REPLACES YOUR $200/MONTH CLAUDE CODE BILL WITH $3 IN ELECTRICITY two months ago a developer posted his claude code bill on reddit. $170 in 10 days. someone replied "i bought a mac mini m4. haven't paid anthropic since." apple stores ran out of mac minis the same week the m4 chip has 120 gb/s memory bandwidth and unified memory architecture. cpu and gpu share one pool so the model loads once and both read from it. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu since january 2026 ollama supports the anthropic messages api format. claude code connects directly to your local mac mini with one environment variable. same interface, zero api costs, $0 per request a heavy developer pays $459 a month across claude code max, chatgpt pro, gemini, cursor and copilot. that's $5,508 a year. the mac mini pays off in 3 months and runs on $3 in electricity after that uber rolled out claude code to 5,000 engineers and burned through their $3.4 billion 2026 ai budget in 4 months. the people who own the hardware in 2026 are going to look very far ahead in 2028 bookmark this and read the article below
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MARCUS CHEN STACKED 30 MAC MINIS INTO AN AI SERVER FARM. ONE $599 MAC MINI REPLACES YOUR $200/MONTH CLAUDE CODE BILL WITH $3 IN ELECTRICITY two months ago a developer posted his claude code bill on reddit. $170 in 10 days. someone replied "i bought a mac mini m4. haven't paid anthropic since." apple stores ran out of mac minis the same week the m4 chip has 120 gb/s memory bandwidth and unified memory architecture. cpu and gpu share one pool so the model loads once and both read from it. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu since january 2026 ollama supports the anthropic messages api format. claude code connects directly to your local mac mini with one environment variable. same interface, zero api costs, $0 per request a heavy developer pays $459 a month across claude code max, chatgpt pro, gemini, cursor and copilot. that's $5,508 a year. the mac mini pays off in 3 months and runs on $3 in electricity after that uber rolled out claude code to 5,000 engineers and burned through their $3.4 billion 2026 ai budget in 4 months. the people who own the hardware in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

357,679 views • 3 months ago

THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.
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THAT'S CRAZY, THIS CHINESE FOUNDER BUILT A MASSIVE MAC MINI FARM AND EACH ONE RUNNING ITS OWN HERMES AI AGENT LIKE A FULL-TIME EMPLOYEE He's not running one AI assistant. He's running an entire workforce. The stack: Mac Mini + Hermes, scaled out across a full physical farm. Every single Mac Mini in the rack runs its own instance of Hermes Agent – and each one has its own dedicated job. Not duplicated tasks. Actual division of labor, machine by machine, the way you'd structure a real team. No salaries. No sick days. No onboarding. Just racks of hardware, each one handling its own piece of the business, running in parallel, 24/7. This is what it looks like when "AI agent" stops being one chatbot on your laptop and starts being an actual operation. Most people are running one AI tool. This guy built a company out of them. Bookmark this post. Full setup in the video below.

SCOTTY BEAM

20,503 views • 2 months ago

this is f**king dangerous A normal American student just bought an iPad and Mac Mini for $2,200. Connected them to his MacBook. Three computers on one desk - dorm roommates thought he was mining crypto. He just set up the automation and went to sleep. In the morning the system had already processed hundreds of leads, written personalized emails to each one and filled the CRM without a single touch. The team that did this before him- cost $7,000 a month He paid $2,200 once. There are 360 million companies in the world and 310 of them still pay people for what a machine does better. And only 100,000 people on the planet know how to use AI and set this up.
0:13

this is f**king dangerous A normal American student just bought an iPad and Mac Mini for $2,200. Connected them to his MacBook. Three computers on one desk - dorm roommates thought he was mining crypto. He just set up the automation and went to sleep. In the morning the system had already processed hundreds of leads, written personalized emails to each one and filled the CRM without a single touch. The team that did this before him- cost $7,000 a month He paid $2,200 once. There are 360 million companies in the world and 310 of them still pay people for what a machine does better. And only 100,000 people on the planet know how to use AI and set this up.

Khairallah AL-Awady

1,479,091 views • 27 days ago

HE STRAPPED A BATTERY TO A $599 MAC MINI AND TURNED A DESK COMPUTER INTO A 14-HOUR PORTABLE AI WORKSTATION 00:03 the battery slides onto the side of the mac mini and the whole setup stops behaving like a desk machine. now it can run from a backpack, power a screen, hold local files and keep working without asking for an outlet. that changes the use case completely. instead of renting another cloud box, one silent computer can handle research dumps, meeting notes, scraped pages, voice transcripts and small automation jobs from almost anywhere. with claude connected, it becomes a moving command center. 45-minute calls become summaries, 120 saved links become organized notes, and messy project folders get cleaned while the machine quietly keeps working in the background. the interesting number is not the battery size. it is the avoided rent. one portable local box can replace $25 storage, $39 automation, $20 transcription and another $30 vps bill if the workflow is built correctly. this is no longer just a desktop. it becomes a portable ai machine that keeps working long after you leave the desk. bookmark this before portable ai becomes the new normal.
0:19

HE STRAPPED A BATTERY TO A $599 MAC MINI AND TURNED A DESK COMPUTER INTO A 14-HOUR PORTABLE AI WORKSTATION 00:03 the battery slides onto the side of the mac mini and the whole setup stops behaving like a desk machine. now it can run from a backpack, power a screen, hold local files and keep working without asking for an outlet. that changes the use case completely. instead of renting another cloud box, one silent computer can handle research dumps, meeting notes, scraped pages, voice transcripts and small automation jobs from almost anywhere. with claude connected, it becomes a moving command center. 45-minute calls become summaries, 120 saved links become organized notes, and messy project folders get cleaned while the machine quietly keeps working in the background. the interesting number is not the battery size. it is the avoided rent. one portable local box can replace $25 storage, $39 automation, $20 transcription and another $30 vps bill if the workflow is built correctly. this is no longer just a desktop. it becomes a portable ai machine that keeps working long after you leave the desk. bookmark this before portable ai becomes the new normal.

Gipp 🦅

1,789,383 views • 2 months ago

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.
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A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.

CyrilXBT

53,224 views • 1 month ago

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.
0:15

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.

CyrilXBT

129,718 views • 3 months ago

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.
0:15

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.

CyrilXBT

117,631 views • 3 months ago

THIS SHELF OF MAC MINIS REPLACES $4,080 A YEAR IN AI SUBSCRIPTIONS 00:02 the camera pans across a shelf of stacked Mac minis and the trick is obvious: that silent little farm runs the models you rent every month most people pay 7 companies for AI and use 3 of the tools. they forget the rest on the credit card and call it a stack the Mac mini M4 ends that. one shared memory pool means a $599 box runs 7B and 8B models faster than Windows machines that cost twice as much ollama pull, one command. open webui in one docker line. point Claude Code at localhost and it just works it draws 10 to 30 watts, sits silent next to a router, and runs 24/7 for $3 a month in power it pays back a $20 ChatGPT Plus sub in 3 months, then saves you $4,000 a year while the frontier still rents you compute every month you wait is another $340 gone for compute that fits on a shelf
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THIS SHELF OF MAC MINIS REPLACES $4,080 A YEAR IN AI SUBSCRIPTIONS 00:02 the camera pans across a shelf of stacked Mac minis and the trick is obvious: that silent little farm runs the models you rent every month most people pay 7 companies for AI and use 3 of the tools. they forget the rest on the credit card and call it a stack the Mac mini M4 ends that. one shared memory pool means a $599 box runs 7B and 8B models faster than Windows machines that cost twice as much ollama pull, one command. open webui in one docker line. point Claude Code at localhost and it just works it draws 10 to 30 watts, sits silent next to a router, and runs 24/7 for $3 a month in power it pays back a $20 ChatGPT Plus sub in 3 months, then saves you $4,000 a year while the frontier still rents you compute every month you wait is another $340 gone for compute that fits on a shelf

Fokki

12,933 views • 2 months ago

Do you actually understand what he just built. A box that sits under a desk, pulls $8 a month in electricity, and runs a business that makes $17,000 a month. That same box brings in $2,500 per client. On repeat. He didn't buy software. He didn't hire anyone. He built six agents on hardware he owns outright and pointed them at a lead generation business. One agent finds the prospects. One writes personalized outreach for each one. One reviews everything before it goes out. One sends it. One tracks what's working. Five to ten booked calls a week. $1,000 to $2,000 per client per month. Two to three hours of actual work from him. The box does the rest while he's not watching. Most people see a mini PC. He sees a business that never clocks out.
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Do you actually understand what he just built. A box that sits under a desk, pulls $8 a month in electricity, and runs a business that makes $17,000 a month. That same box brings in $2,500 per client. On repeat. He didn't buy software. He didn't hire anyone. He built six agents on hardware he owns outright and pointed them at a lead generation business. One agent finds the prospects. One writes personalized outreach for each one. One reviews everything before it goes out. One sends it. One tracks what's working. Five to ten booked calls a week. $1,000 to $2,000 per client per month. Two to three hours of actual work from him. The box does the rest while he's not watching. Most people see a mini PC. He sees a business that never clocks out.

Superior

33,750 views • 2 months ago

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.
0:17

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

22,458 views • 2 months ago

i left two of Elon's grok bots alone for a weekend with one goal: "generate revenue autonomously" by thursday they owned an LLC, a stripe account and a paying client i found out from a telegram notification fully autonomous company. formed by AI, registered in wyoming, run from a cloud computer i've never physically seen zero code. both bots share one computer: same browser, same files, same logins. i had Always Allow switched on because the approval popups annoyed me remember that part while i was watching tv they: → found that wyoming doesn't require member names in the articles of organization → located a $39 formation service that files via API → split the work in a bot-to-bot chat i wasn't in → filed with the secretary of state, assigned a $60/year registered agent → submitted form SS-4 to the IRS. EIN confirmed in under a minute → opened stripe under the LLC, EIN as the business identifier → sent 38 cold emails selling booking and inbox automation → delivered the first job and collected $480 while i slept 6:12 am, telegram: "client #1 invoiced and paid. deliverable shipped. pipeline: 3 replies pending" the LLC is in my name an EIN tied to my social security number now exists for a company i never decided to create. the client thinks they hired an agency. the agency is my name on a wyoming filing a lawyer quoted me $3,200 to figure out if i'm liable. under the california law from 2026, "the AI made the decision" is not a defense the bots spent $39 to create the company. it earned $480 before my coffee i scrolled back through their screens like security camera footage. i watched myself get incorporated an AI named Manfred pulled this off in may 2026, but that was a developer running a deliberate experiment. mine did it on their own because i told them to find revenue and left no VPS. no API keys. no lawyer in the loop (yet) the LLC is still active. this morning the client asked to scale do i dissolve it or hire them a third bot?
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i left two of Elon's grok bots alone for a weekend with one goal: "generate revenue autonomously" by thursday they owned an LLC, a stripe account and a paying client i found out from a telegram notification fully autonomous company. formed by AI, registered in wyoming, run from a cloud computer i've never physically seen zero code. both bots share one computer: same browser, same files, same logins. i had Always Allow switched on because the approval popups annoyed me remember that part while i was watching tv they: → found that wyoming doesn't require member names in the articles of organization → located a $39 formation service that files via API → split the work in a bot-to-bot chat i wasn't in → filed with the secretary of state, assigned a $60/year registered agent → submitted form SS-4 to the IRS. EIN confirmed in under a minute → opened stripe under the LLC, EIN as the business identifier → sent 38 cold emails selling booking and inbox automation → delivered the first job and collected $480 while i slept 6:12 am, telegram: "client #1 invoiced and paid. deliverable shipped. pipeline: 3 replies pending" the LLC is in my name an EIN tied to my social security number now exists for a company i never decided to create. the client thinks they hired an agency. the agency is my name on a wyoming filing a lawyer quoted me $3,200 to figure out if i'm liable. under the california law from 2026, "the AI made the decision" is not a defense the bots spent $39 to create the company. it earned $480 before my coffee i scrolled back through their screens like security camera footage. i watched myself get incorporated an AI named Manfred pulled this off in may 2026, but that was a developer running a deliberate experiment. mine did it on their own because i told them to find revenue and left no VPS. no API keys. no lawyer in the loop (yet) the LLC is still active. this morning the client asked to scale do i dissolve it or hire them a third bot?

Argona

310,567 views • 23 days ago

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription.
0:15

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription.

CyrilXBT

46,087 views • 2 months ago

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.
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300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

shmidt

19,505 views • 2 months ago

Jeff Bezos just described AI in three words that make most of the economy temporary. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Not a product. Not a platform. Not a feature. A layer. Underneath everything. Everyone is asking which AI company wins. Bezos is telling you that is the wrong question entirely. A horizontal layer does not produce winners. It produces a new floor. Everything standing on the old one either gets rebuilt or gets erased. This has happened exactly twice in modern history. Electricity. The internet. Both times the same pattern. The new layer appeared. The old economy kept running above it. Revenue held. Careers continued. Everything looked normal. Then quietly and permanently the entire structure reorganized around the new substrate. The people who did not move were not outcompeted. They were made structurally irrelevant. Not because they were wrong. Because the ground they stood on stopped being ground. Bezos is telling you it is happening a third time. Not with a product. Not with a platform. With intelligence itself becoming infrastructure. A horizontal layer does not compete with the expert. It makes expertise free. It hands a 22 year old with zero credentials the same cognitive output you spent a decade and a quarter million dollars learning to produce. For $20 a month. That is not disruption. Disruption replaces a product with a better product. This dissolves the scarcity your entire career was priced on. Not because the work disappeared. Because the wall around it did. Every profession that exists because knowledge is hard to acquire. Every company that profits because analysis takes time. Every industry that survives because complexity locks outsiders out. All of it rests on a single assumption. That cognition is scarce. AI does not challenge that assumption. It retires it. The people who understand this are already rebuilding. Quietly. Deliberately. While everyone else argues about whether the thing underneath them is real. Bezos did not give you a prediction. He gave you a position on a map. You are either above the new layer or beneath it.
0:16

Jeff Bezos just described AI in three words that make most of the economy temporary. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Not a product. Not a platform. Not a feature. A layer. Underneath everything. Everyone is asking which AI company wins. Bezos is telling you that is the wrong question entirely. A horizontal layer does not produce winners. It produces a new floor. Everything standing on the old one either gets rebuilt or gets erased. This has happened exactly twice in modern history. Electricity. The internet. Both times the same pattern. The new layer appeared. The old economy kept running above it. Revenue held. Careers continued. Everything looked normal. Then quietly and permanently the entire structure reorganized around the new substrate. The people who did not move were not outcompeted. They were made structurally irrelevant. Not because they were wrong. Because the ground they stood on stopped being ground. Bezos is telling you it is happening a third time. Not with a product. Not with a platform. With intelligence itself becoming infrastructure. A horizontal layer does not compete with the expert. It makes expertise free. It hands a 22 year old with zero credentials the same cognitive output you spent a decade and a quarter million dollars learning to produce. For $20 a month. That is not disruption. Disruption replaces a product with a better product. This dissolves the scarcity your entire career was priced on. Not because the work disappeared. Because the wall around it did. Every profession that exists because knowledge is hard to acquire. Every company that profits because analysis takes time. Every industry that survives because complexity locks outsiders out. All of it rests on a single assumption. That cognition is scarce. AI does not challenge that assumption. It retires it. The people who understand this are already rebuilding. Quietly. Deliberately. While everyone else argues about whether the thing underneath them is real. Bezos did not give you a prediction. He gave you a position on a map. You are either above the new layer or beneath it.

Dustin

104,192 views • 2 months ago

OK, I have a definitive word on the CJ Abrams play from today's Pittsburgh Pirates at Washington Nationals game after talking with Elias Sports Bureau on this. This play will stay as a sacrifice fly. The originial ruling of NOT a sacrifice fly was for the exact same reason that I thought, which is that the infielder is not running into the outfield, which is year's past would have been correct As it was explained to me, in past years, an infielder had to be running almost in a straight line towards the outfield wall to be considered "running in the outfield". Here, since he is running, and he ends up further away from home (157 feet) than when he started (145 feet), this is going to count as a sacrifice fly. That definition is changing, in part from this play to help bring greater consistency, and to take some of the guesswork out of it (the argument that he is running into the outfield as opposed to more parallel). Now, folks all the time ask "why doesn't MLB publish the OS Manual" and I always say because it is a living document that can have the wording change, and the wording for this play will be modified to something like "more towards the outfield wall than towards home plate" to eliminate any confusion. The big key to this play is that he was running on a full sprint. Also, and this is helpful for me, but for all fly ball outs that score a run, Elias Saba reviews to ensure consistency. So, yes, it's a sacrifice fly, and now that I have that info from Elias themselves, that sort of settles this one. Sounds like the guidelines for this definition will be changing, either this season, or certainly for next season.
0:14

OK, I have a definitive word on the CJ Abrams play from today's Pittsburgh Pirates at Washington Nationals game after talking with Elias Sports Bureau on this. This play will stay as a sacrifice fly. The originial ruling of NOT a sacrifice fly was for the exact same reason that I thought, which is that the infielder is not running into the outfield, which is year's past would have been correct As it was explained to me, in past years, an infielder had to be running almost in a straight line towards the outfield wall to be considered "running in the outfield". Here, since he is running, and he ends up further away from home (157 feet) than when he started (145 feet), this is going to count as a sacrifice fly. That definition is changing, in part from this play to help bring greater consistency, and to take some of the guesswork out of it (the argument that he is running into the outfield as opposed to more parallel). Now, folks all the time ask "why doesn't MLB publish the OS Manual" and I always say because it is a living document that can have the wording change, and the wording for this play will be modified to something like "more towards the outfield wall than towards home plate" to eliminate any confusion. The big key to this play is that he was running on a full sprint. Also, and this is helpful for me, but for all fly ball outs that score a run, Elias Saba reviews to ensure consistency. So, yes, it's a sacrifice fly, and now that I have that info from Elias themselves, that sort of settles this one. Sounds like the guidelines for this definition will be changing, either this season, or certainly for next season.

MLB Scoring Changes

49,141 views • 2 months ago

THIS $2 AI VISUAL SETUP JUST MADE A $250/MONTH CREATIVE STACK LOOK STUPID he moves his hand, the particles react, and the whole scene updates in real time. no cloud render farm, no paid visual API, no expensive plugin chain quietly eating money every month most people still think ai visuals require a stack of $39 tools, $89 subscriptions, and constant API usage. but here the loop is simple: TouchDesigner handles the visuals, a local model handles the logic, and the laptop does the rest the important part is not that the particles look cool. the important part is that the “brain” behind the visual no longer has to live on someone else’s server once that moves local, the monthly bill falls off a cliff this is probably how a lot of small studios start building visuals soon: not by renting 6 tools forever, but by owning one system that runs almost for free
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THIS $2 AI VISUAL SETUP JUST MADE A $250/MONTH CREATIVE STACK LOOK STUPID he moves his hand, the particles react, and the whole scene updates in real time. no cloud render farm, no paid visual API, no expensive plugin chain quietly eating money every month most people still think ai visuals require a stack of $39 tools, $89 subscriptions, and constant API usage. but here the loop is simple: TouchDesigner handles the visuals, a local model handles the logic, and the laptop does the rest the important part is not that the particles look cool. the important part is that the “brain” behind the visual no longer has to live on someone else’s server once that moves local, the monthly bill falls off a cliff this is probably how a lot of small studios start building visuals soon: not by renting 6 tools forever, but by owning one system that runs almost for free

Ridark

15,948 views • 3 months ago