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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,...

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A startup in China packed roughly 1,000 Mac Mini M4 computers into a single data center to run AI workloads without paying ongoing cloud fees. The base Mac Mini M4 starts at $599 and draws just 10 to 30 watts under load, a fraction of the 300 to 500 watts a traditional GPU server pulls.
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A startup in China packed roughly 1,000 Mac Mini M4 computers into a single data center to run AI workloads without paying ongoing cloud fees. The base Mac Mini M4 starts at $599 and draws just 10 to 30 watts under load, a fraction of the 300 to 500 watts a traditional GPU server pulls.

Massimo

2,179,794 Aufrufe • vor 2 Monaten

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

69,106 Aufrufe • vor 2 Monaten

1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.
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1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.

AiMind

82,647 Aufrufe • vor 1 Monat

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 Aufrufe • vor 3 Monaten

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

358,026 Aufrufe • vor 3 Monaten

the thing you rent for $200 a month just became something you can own for $1,700 once but the money is not even the real story for the first time a 200 billion parameter model is not in a datacenter, it is sitting on a desk the cloud spent years convincing you a model this size needed their servers, their meter, their monthly bill people are stacking four subscriptions into a $440 a month bill to rent what one box this size now owns outright it needed a box the size of a book the moment the model moves from their datacenter to your desk, the whole game changes it stops being about who has the best AI it becomes about who ships it on every desk the cloud told you this needed a datacenter it needed a desk i did the full math on what this kills in the article below
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the thing you rent for $200 a month just became something you can own for $1,700 once but the money is not even the real story for the first time a 200 billion parameter model is not in a datacenter, it is sitting on a desk the cloud spent years convincing you a model this size needed their servers, their meter, their monthly bill people are stacking four subscriptions into a $440 a month bill to rent what one box this size now owns outright it needed a box the size of a book the moment the model moves from their datacenter to your desk, the whole game changes it stops being about who has the best AI it becomes about who ships it on every desk the cloud told you this needed a datacenter it needed a desk i did the full math on what this kills in the article below

John Doe

26,096 Aufrufe • vor 3 Monaten

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 agent running entirely through Ollama, done in under an hour. Zero cloud dependency, no API bills, no monthly charges bleeding the client dry. The coffee shop owner gets a private AI system that keeps working even if the WiFi dies, and he walks out with $2,100 for an install that takes less time than a long lunch. The hardware cost him $400. One deployment and the machine's already paid for five times over. Then he locks in a monthly retainer for support, somewhere around $100-150, which means every client after the first is close to pure margin stacking on top of recurring revenue. Most people hear "AI business" and think they need to build a SaaS platform or learn to code or raise funding from someone. This skips all of that and goes straight to walking into coffee shops with a Mac mini under one arm. Not a company that scales to a billion dollars, obviously, but a solo operator clearing a few thousand a month from local installs while everyone else is still arguing about which LLM is best on Twitter.
0:11

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 agent running entirely through Ollama, done in under an hour. Zero cloud dependency, no API bills, no monthly charges bleeding the client dry. The coffee shop owner gets a private AI system that keeps working even if the WiFi dies, and he walks out with $2,100 for an install that takes less time than a long lunch. The hardware cost him $400. One deployment and the machine's already paid for five times over. Then he locks in a monthly retainer for support, somewhere around $100-150, which means every client after the first is close to pure margin stacking on top of recurring revenue. Most people hear "AI business" and think they need to build a SaaS platform or learn to code or raise funding from someone. This skips all of that and goes straight to walking into coffee shops with a Mac mini under one arm. Not a company that scales to a billion dollars, obviously, but a solo operator clearing a few thousand a month from local installs while everyone else is still arguing about which LLM is best on Twitter.

BrainRul

4,703,307 Aufrufe • vor 1 Monat

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 Aufrufe • vor 2 Monaten

THIS $599 MAC MINI CAN DRIVE THREE DISPLAYS NATIVELY - THIS SETUP TOOK "MORE SCREEN SPACE" SO FAR IT ENDED WITH BINOCULARS. the M4 Mac mini shrinks a full desktop into a 5 x 5-inch box. the base model launched with: 10-core CPU 10-core GPU 16GB unified memory support for two 6K displays plus one 5K display the M4 Pro version can drive three 6K displays at 60Hz, pushing more than 60 million pixels at once. no DisplayLink software is required for the supported three-screen configuration. the video turns that spec into a monitor wall, then delivers the punchline when the creator reaches for binoculars. honest line: Apple guarantees up to three native displays. the clip does not prove every screen in the room is connected to this one Mac mini. the tiny computer solved the screen limit. the next bottleneck is finding the window you opened. bookmark & watch today ↓
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THIS $599 MAC MINI CAN DRIVE THREE DISPLAYS NATIVELY - THIS SETUP TOOK "MORE SCREEN SPACE" SO FAR IT ENDED WITH BINOCULARS. the M4 Mac mini shrinks a full desktop into a 5 x 5-inch box. the base model launched with: 10-core CPU 10-core GPU 16GB unified memory support for two 6K displays plus one 5K display the M4 Pro version can drive three 6K displays at 60Hz, pushing more than 60 million pixels at once. no DisplayLink software is required for the supported three-screen configuration. the video turns that spec into a monitor wall, then delivers the punchline when the creator reaches for binoculars. honest line: Apple guarantees up to three native displays. the clip does not prove every screen in the room is connected to this one Mac mini. the tiny computer solved the screen limit. the next bottleneck is finding the window you opened. bookmark & watch today ↓

Grimmer

16,290 Aufrufe • vor 1 Monat

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 Aufrufe • vor 3 Monaten

This box holds 300TB with no subscription. Five years ago, that took a server room. A separate room, a cabinet the height of a person, and an electricity bill visible from space. Now it is one case on a desk. 10 bays for 3.5-inch HDDs. Pull a tray, click a drive in, slide it back. Plus 30TB. Repeat until you reach 300TB. The back panel comes off, and under it sit 2 M.2 slots and a RAM slot. Not a sealed brick, an actual motherboard you service yourself. The NVMe drives hold cache and apps. The HDDs hold the archive. You add RAM the day it starts to matter. Pay for the hardware once, and it is yours. Nobody raises your plan, trims your limits, or locks your access over terms you never read. 300TB with no bill arriving every month. The server room did not disappear. It just fit into one case.
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This box holds 300TB with no subscription. Five years ago, that took a server room. A separate room, a cabinet the height of a person, and an electricity bill visible from space. Now it is one case on a desk. 10 bays for 3.5-inch HDDs. Pull a tray, click a drive in, slide it back. Plus 30TB. Repeat until you reach 300TB. The back panel comes off, and under it sit 2 M.2 slots and a RAM slot. Not a sealed brick, an actual motherboard you service yourself. The NVMe drives hold cache and apps. The HDDs hold the archive. You add RAM the day it starts to matter. Pay for the hardware once, and it is yours. Nobody raises your plan, trims your limits, or locks your access over terms you never read. 300TB with no bill arriving every month. The server room did not disappear. It just fit into one case.

AiMind

15,985 Aufrufe • vor 28 Tagen

SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?
0:14

SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?

kocer

591,647 Aufrufe • vor 2 Monaten

Everyone assumes serious AI compute means renting someone else's datacenter This is the datacenter 1,000 Mac Mini M4s on steel shelves $599 each, paid once Replacing a $14K a month cloud GPU bill It started much smaller A dev posted his Claude Code bill, $170 in 10 days The top reply got bigger than the post "I bought a Mac Mini M4, haven't paid Anthropic since" 10-30 watts a box instead of 300-500 120 GB/s unified memory, the model loads once Ollama now speaks the Anthropic Messages API So Claude Code can point at the box under your desk instead of Anthropic's servers Nobody claims these beat frontier models They claim most of your prompts never needed one The bill was never the price of intelligence It's the price of renting it for work that never needed renting Full breakdown below
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Everyone assumes serious AI compute means renting someone else's datacenter This is the datacenter 1,000 Mac Mini M4s on steel shelves $599 each, paid once Replacing a $14K a month cloud GPU bill It started much smaller A dev posted his Claude Code bill, $170 in 10 days The top reply got bigger than the post "I bought a Mac Mini M4, haven't paid Anthropic since" 10-30 watts a box instead of 300-500 120 GB/s unified memory, the model loads once Ollama now speaks the Anthropic Messages API So Claude Code can point at the box under your desk instead of Anthropic's servers Nobody claims these beat frontier models They claim most of your prompts never needed one The bill was never the price of intelligence It's the price of renting it for work that never needed renting Full breakdown below

Skaly_Bull

10,597 Aufrufe • vor 1 Monat

You've probably scrolled past a dozen posts about Jev this week without anyone telling you what it actually is. It's the first model from TypeSafe, a lab started by one of the researchers behind ChatGPT. It's a decision engine: you give it options, it picks one and tells you how sure it is. It cannot write a single word, and that is the interesting part. Every other AI you use writes. That is the whole interface. So when software needs a plain yes or no, we make a model write a paragraph and then dig the answer back out of it. Fine in a chat window where a human reads it. Bad inside software, where code has to act on it. The bet is that the valuable half was never the writing. It was the deciding. That problem showed up in WordPress years ago, and it is the reason WPVibe works the way it does. The AI does the work. Anything permanent stops and waits, because a delete that skips the trash is not something software should decide on its own.
0:14

You've probably scrolled past a dozen posts about Jev this week without anyone telling you what it actually is. It's the first model from TypeSafe, a lab started by one of the researchers behind ChatGPT. It's a decision engine: you give it options, it picks one and tells you how sure it is. It cannot write a single word, and that is the interesting part. Every other AI you use writes. That is the whole interface. So when software needs a plain yes or no, we make a model write a paragraph and then dig the answer back out of it. Fine in a chat window where a human reads it. Bad inside software, where code has to act on it. The bet is that the valuable half was never the writing. It was the deciding. That problem showed up in WordPress years ago, and it is the reason WPVibe works the way it does. The AI does the work. Anything permanent stops and waits, because a delete that skips the trash is not something software should decide on its own.

John Turner

21,029 Aufrufe • vor 8 Tagen

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.
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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.

CyrilXBT

46,087 Aufrufe • vor 2 Monaten

Want full control over the OpenClaw/Hermes Agent on your Mac Mini? Looking to build a Mac Mini Cluster with remote physical power control? Try #NanoKVM-Go! A single USB-C connection is all you need for complete remote access and Fingerbot power control!👇
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Want full control over the OpenClaw/Hermes Agent on your Mac Mini? Looking to build a Mac Mini Cluster with remote physical power control? Try #NanoKVM-Go! A single USB-C connection is all you need for complete remote access and Fingerbot power control!👇

Sipeed

22,660 Aufrufe • vor 3 Monaten

Jeff Bezos just told you exactly how to price AI. Nobody listened. 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. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.
0:16

Jeff Bezos just told you exactly how to price AI. Nobody listened. 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. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.

Dustin

542,261 Aufrufe • vor 5 Monaten

This is not a border dispute. It is a sermon. A Hamas leader on a Gaza stage tells seven million Palestinians abroad to stop warming up. There are Jews everywhere, he says. Attack every Jew on Earth. Slaughter them. Kill them. With Allah’s help. The crowd is not a war room. It is a public. Hamas did not invent that sentence. Hamas is but one franchise of it. Islamic Jihad says the same thing with a different logo. Hezbollah wraps it in Khomeini and the language of “the Zionist entity.” The Houthis put “death to Israel, curse the Jews” on a flag and call it governance. The regime in Tehran funds the network and calls the Jewish state a tumor. Different uniforms. Same theology. For them, Jewish sovereignty is an insult to Allah, and Jewish lives outside the land are not off-limits. That is why “from the river to the sea” is not a housing policy, and why October 7 was not an accident of occupation. The target list in this clip is not a soldier at a checkpoint. It is Jews as such, wherever they are. Once the enemy is a people, not a government, there is no ceasefire that satisfies the idea. There is only a pause. Western coverage keeps shrinking this to one militia and one strip of coast because a regional ideology is harder to manage than a “peace process.” Factions are useful that way. They let you condemn Hamas on Tuesday and treat Hezbollah as Lebanese politics on Wednesday and the Houthis as a shipping problem on Thursday. The preacher does not bother with those folders. He names the Jews and asks the diaspora to start. If you want to understand the war, start with what they say when they are not fundraising in English. The map they want is not two states. It is a world with fewer Jews in it, sanctified as duty. Hamas is the local office. The ideology is the corporation.
0:12

This is not a border dispute. It is a sermon. A Hamas leader on a Gaza stage tells seven million Palestinians abroad to stop warming up. There are Jews everywhere, he says. Attack every Jew on Earth. Slaughter them. Kill them. With Allah’s help. The crowd is not a war room. It is a public. Hamas did not invent that sentence. Hamas is but one franchise of it. Islamic Jihad says the same thing with a different logo. Hezbollah wraps it in Khomeini and the language of “the Zionist entity.” The Houthis put “death to Israel, curse the Jews” on a flag and call it governance. The regime in Tehran funds the network and calls the Jewish state a tumor. Different uniforms. Same theology. For them, Jewish sovereignty is an insult to Allah, and Jewish lives outside the land are not off-limits. That is why “from the river to the sea” is not a housing policy, and why October 7 was not an accident of occupation. The target list in this clip is not a soldier at a checkpoint. It is Jews as such, wherever they are. Once the enemy is a people, not a government, there is no ceasefire that satisfies the idea. There is only a pause. Western coverage keeps shrinking this to one militia and one strip of coast because a regional ideology is harder to manage than a “peace process.” Factions are useful that way. They let you condemn Hamas on Tuesday and treat Hezbollah as Lebanese politics on Wednesday and the Houthis as a shipping problem on Thursday. The preacher does not bother with those folders. He names the Jews and asks the diaspora to start. If you want to understand the war, start with what they say when they are not fundraising in English. The map they want is not two states. It is a world with fewer Jews in it, sanctified as duty. Hamas is the local office. The ideology is the corporation.

Mor Edge Insight

74,915 Aufrufe • vor 14 Tagen

THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?
0:13

THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?

Framez

18,004 Aufrufe • vor 1 Monat