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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...

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Ridark

7,880 subscribers

15,948 次观看 • 5 个月前 •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.
0:11

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 🦅

591,712 次观看 • 5 个月前

$300/month for AI visuals. replaced by a laptop and $2 electricity bill TouchDesigner + Ollama. local AI model. runs offline. nothing sent to any server. no API key that expires mid-performance > Ollama: 3 commands to install. one line change in existing code > Llama 3.2: real-time parameter calls. fast enough you don’t notice latency > TouchDesigner: hand tracking. audio-reactive. particle systems. generative graphics month one savings: $148-338. every month after: same your laptop. $0/month. a visual studio that runs forever
0:16

$300/month for AI visuals. replaced by a laptop and $2 electricity bill TouchDesigner + Ollama. local AI model. runs offline. nothing sent to any server. no API key that expires mid-performance > Ollama: 3 commands to install. one line change in existing code > Llama 3.2: real-time parameter calls. fast enough you don’t notice latency > TouchDesigner: hand tracking. audio-reactive. particle systems. generative graphics month one savings: $148-338. every month after: same your laptop. $0/month. a visual studio that runs forever

NO1ennn

30,177 次观看 • 5 个月前

A 25-year-old creator from Miami built an AI girl that now brings in $52,000 a month. No agency. No real model. No filming crew. Just Claude running the personality, AI generating the visuals, and a system publishing content every day. The girl appears in luxury hotels, beach clubs, apartments, and brand campaigns without ever leaving a laptop. Followers keep watching. Brands keep paying. The account never gets tired, misses a shoot, or disappears for a week. Most people think the opportunity is creating a realistic face. The real money is building a character that can produce unlimited attention.
0:14

A 25-year-old creator from Miami built an AI girl that now brings in $52,000 a month. No agency. No real model. No filming crew. Just Claude running the personality, AI generating the visuals, and a system publishing content every day. The girl appears in luxury hotels, beach clubs, apartments, and brand campaigns without ever leaving a laptop. Followers keep watching. Brands keep paying. The account never gets tired, misses a shoot, or disappears for a week. Most people think the opportunity is creating a realistic face. The real money is building a character that can produce unlimited attention.

psinaaa

245,753 次观看 • 3 个月前

212,000 people stopped scrolling for a staircase. that's not luck. that's what happens when the visual is right. real estate has always sold on emotion. the problem was getting the visual in front of enough people. AI just solved that part. one scan. one video. organic reach to thousands of buyers. no agency. no crew. no $2,000 shoot. the full breakdown is in the article below.
0:13

212,000 people stopped scrolling for a staircase. that's not luck. that's what happens when the visual is right. real estate has always sold on emotion. the problem was getting the visual in front of enough people. AI just solved that part. one scan. one video. organic reach to thousands of buyers. no agency. no crew. no $2,000 shoot. the full breakdown is in the article below.

Dep

16,740 次观看 • 6 个月前

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.
0:13

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.

Darshal Jaitwar

141,038 次观看 • 10 个月前

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

22,522 次观看 • 4 个月前

$0.003 per second for video generation, without compromising on speed or visual quality? The supplied comparisons put Vivix W1 alongside leading models on visual quality. It also delivers eight seconds of video in roughly eight seconds. But the bigger story is that W1 is a real-time interactive video model. Every extra minute of interaction means more video to generate and pay for. Making generation this affordable could make interactive stories and live visuals practical to run, not just impressive demos. Live visuals are what I’m most curious about. Generating quickly is one thing; reacting at the right moment is what would make them feel live. Vivix.AI already offers real-time generation through the API; the browser playground currently produces finished clips. A closer look at what could power those live visuals 👇
0:10

$0.003 per second for video generation, without compromising on speed or visual quality? The supplied comparisons put Vivix W1 alongside leading models on visual quality. It also delivers eight seconds of video in roughly eight seconds. But the bigger story is that W1 is a real-time interactive video model. Every extra minute of interaction means more video to generate and pay for. Making generation this affordable could make interactive stories and live visuals practical to run, not just impressive demos. Live visuals are what I’m most curious about. Generating quickly is one thing; reacting at the right moment is what would make them feel live. Vivix.AI already offers real-time generation through the API; the browser playground currently produces finished clips. A closer look at what could power those live visuals 👇

Kalsoom (ghotai )

71,868 次观看 • 1 个月前

THIS GUY BUILT A MINI AI FARM OUT OF 4 NVIDIA BOXES. IT DOESN'T 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. 4 BOXES. 512GB OF UNIFIED MEMORY. NEARLY $12,000 OF LOCAL AI COMPUTE SITTING ON ONE DESK. NO CLOUD GPU RENTAL FEES. NO HOURLY METER. NO RENTED COMPUTE EATING YOUR MARGINS. MOST PEOPLE STILL THINK LOCAL AI MEANS A SLOW LAPTOP RUNNING A TOY MODEL. MEANWHILE, PEOPLE ARE STACKING SERIOUS AI COMPUTE AT HOME. LOCAL AI IS STARTING TO LOOK LIKE THE NEW MINING FARM.
0:11

THIS GUY BUILT A MINI AI FARM OUT OF 4 NVIDIA BOXES. IT DOESN'T 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. 4 BOXES. 512GB OF UNIFIED MEMORY. NEARLY $12,000 OF LOCAL AI COMPUTE SITTING ON ONE DESK. NO CLOUD GPU RENTAL FEES. NO HOURLY METER. NO RENTED COMPUTE EATING YOUR MARGINS. MOST PEOPLE STILL THINK LOCAL AI MEANS A SLOW LAPTOP RUNNING A TOY MODEL. MEANWHILE, PEOPLE ARE STACKING SERIOUS AI COMPUTE AT HOME. LOCAL AI IS STARTING TO LOOK LIKE THE NEW MINING FARM.

Vivek Sen

31,812 次观看 • 3 个月前

WHY ARE WE STILL ALLOWING BILL GATES TO THINK HE CAN RULE THE REST OVER THE REST OF US? WHO GAVE GATES THE RIGHT TO DECIDE WHAT HUMAN BEINGS STILL MATTER AND WHICH ONES DO NOT? Bill Gates just said humans won’t be needed for most things. And that ”we’ll decide” who still matters. WHO IS THE 'WE'? Let that sit for a second. The man who helped build the digital world is now casually announcing that the people living in it might be optional. No panic. No apology. Just a quiet admission from someone who has never had to worry about being replaced. The scariest part is not the AI. It’s the ”we.” Who is ”we,” Bill? Because it is not the people whose jobs disappear next year. This is not a tech problem. It’s a power problem dressed up as progress. When the people building the tools also decide who needs them, the rest of us are just passengers. Do you trust the people at the top to make that call for you? Courtesy - Captains Obvious
0:14

WHY ARE WE STILL ALLOWING BILL GATES TO THINK HE CAN RULE THE REST OVER THE REST OF US? WHO GAVE GATES THE RIGHT TO DECIDE WHAT HUMAN BEINGS STILL MATTER AND WHICH ONES DO NOT? Bill Gates just said humans won’t be needed for most things. And that ”we’ll decide” who still matters. WHO IS THE 'WE'? Let that sit for a second. The man who helped build the digital world is now casually announcing that the people living in it might be optional. No panic. No apology. Just a quiet admission from someone who has never had to worry about being replaced. The scariest part is not the AI. It’s the ”we.” Who is ”we,” Bill? Because it is not the people whose jobs disappear next year. This is not a tech problem. It’s a power problem dressed up as progress. When the people building the tools also decide who needs them, the rest of us are just passengers. Do you trust the people at the top to make that call for you? Courtesy - Captains Obvious

BelannF

14,510 次观看 • 7 个月前

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

591,744 次观看 • 4 个月前

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.
0:10

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 次观看 • 6 个月前

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.
0:11

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

82,816 次观看 • 2 个月前

Cancelled ChatGPT -> Built JARVIS -> Pays $0 -> it works offline + it's smarter than the $20/month version. No WiFi needed, no cloud, no API keys, no rate limits, no queues, no $20/month just to ask a server in Virginia for the weather. Just a local model running directly on the laptop hardware, voice activated, system integrated, controlling apps, answering questions, doing the work. Iron Man had JARVIS embedded in his suit, this guy has it embedded in his MacBook and it works on a plane, in a basement, on a remote cabin with zero signal. OpenAI is burning $700,000 a day on infrastructure to deliver something this guy runs for free. Anthropic charges $200/month for unlimited Claude access, microsoft built Copilot into every product they sell. This guy skipped all of it, downloaded a model and made his laptop the smartest device in the room. No subscription. No login. No internet. No data sent anywhere ever. The most powerful AI assistant on earth is now the one running locally on hardware you already own. ChatGPT charges you to think slower, he pays nothing and thinks alone, he made it himself.
0:15

Cancelled ChatGPT -> Built JARVIS -> Pays $0 -> it works offline + it's smarter than the $20/month version. No WiFi needed, no cloud, no API keys, no rate limits, no queues, no $20/month just to ask a server in Virginia for the weather. Just a local model running directly on the laptop hardware, voice activated, system integrated, controlling apps, answering questions, doing the work. Iron Man had JARVIS embedded in his suit, this guy has it embedded in his MacBook and it works on a plane, in a basement, on a remote cabin with zero signal. OpenAI is burning $700,000 a day on infrastructure to deliver something this guy runs for free. Anthropic charges $200/month for unlimited Claude access, microsoft built Copilot into every product they sell. This guy skipped all of it, downloaded a model and made his laptop the smartest device in the room. No subscription. No login. No internet. No data sent anywhere ever. The most powerful AI assistant on earth is now the one running locally on hardware you already own. ChatGPT charges you to think slower, he pays nothing and thinks alone, he made it himself.

Defileo🔮

154,800 次观看 • 6 个月前

A guy from China just built a system that reshapes thousands of glowing particles into a jellyfish, a dragon, a statue, and a samurai. Just by moving his hands in front of a camera. Just a webcam reading his hand position. Every particle recalculates in real time. 60 frames per second. Not pre-rendered. Not a recording. Live. Clench both fists and the entire thing collapses into nothing. The whole setup runs on a regular camera and a GPU particle system. No special hardware. This is where hand tracking, computer vision, and real-time graphics have gotten. And most people haven't noticed.
0:14

A guy from China just built a system that reshapes thousands of glowing particles into a jellyfish, a dragon, a statue, and a samurai. Just by moving his hands in front of a camera. Just a webcam reading his hand position. Every particle recalculates in real time. 60 frames per second. Not pre-rendered. Not a recording. Live. Clench both fists and the entire thing collapses into nothing. The whole setup runs on a regular camera and a GPU particle system. No special hardware. This is where hand tracking, computer vision, and real-time graphics have gotten. And most people haven't noticed.

Vaibhav Sisinty

18,334 次观看 • 3 个月前

A 19-YEAR-OLD FROM CANADA TURNED TWERK CLIPS INTO A $6,800/MONTH AI PAGE. Mint hair. Back turned to the camera. Soft daylight, a balcony view, and 12 seconds of movement built almost entirely around one thing: scroll-stopping motion. She dances, twerks, runs her hands through her hair, and gives the kind of clip that people replay before they even decide whether she is real. That is the whole edge. The operator behind the page understood that in this niche, the first win is not storytelling, it is interruption. If the movement stops the thumb for half a second, the algorithm does the rest. The page is run like a funnel, not like a normal content account. Short clips like this go out free on Instagram and TikTok, usually 3–5 times a day, with the best performers pushed again in slightly different versions. One character, one recognizable look, one consistent vibe. The traffic then gets pushed into a paid page where subscriptions sit between $9.99 and $16.99, with extra revenue coming from tips and locked content. On numbers like these, a page can realistically stack up to around 410 paying subs at an average of $11.50, plus $1,900 in PPV and tips, which is how a single AI girl built around dance content gets to roughly $6,800/month. What makes this work is not just that she is attractive. Thousands of AI girls are attractive now. What works is that the content is built for rewatch. Twerking clips, especially from a back-facing angle like this, are simple, fast, and instantly understood by the viewer. There is no setup needed. No explanation. No context. Just motion, attention, and curiosity. People replay it, send it, comment on whether she is real, and that creates the exact kind of engagement these pages live on. The catch, as always, is retention. A clip like this can bring in the spike, but the money only stays if the character keeps posting and keeps feeling consistent. That is why the smarter operators lock the identity, keep the same hair, same body language, same style, and turn one good-performing angle into a repeatable system. One AI girl, one signature dance style, and one content loop that turns short clips into about $6.8K a month.
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A 19-YEAR-OLD FROM CANADA TURNED TWERK CLIPS INTO A $6,800/MONTH AI PAGE. Mint hair. Back turned to the camera. Soft daylight, a balcony view, and 12 seconds of movement built almost entirely around one thing: scroll-stopping motion. She dances, twerks, runs her hands through her hair, and gives the kind of clip that people replay before they even decide whether she is real. That is the whole edge. The operator behind the page understood that in this niche, the first win is not storytelling, it is interruption. If the movement stops the thumb for half a second, the algorithm does the rest. The page is run like a funnel, not like a normal content account. Short clips like this go out free on Instagram and TikTok, usually 3–5 times a day, with the best performers pushed again in slightly different versions. One character, one recognizable look, one consistent vibe. The traffic then gets pushed into a paid page where subscriptions sit between $9.99 and $16.99, with extra revenue coming from tips and locked content. On numbers like these, a page can realistically stack up to around 410 paying subs at an average of $11.50, plus $1,900 in PPV and tips, which is how a single AI girl built around dance content gets to roughly $6,800/month. What makes this work is not just that she is attractive. Thousands of AI girls are attractive now. What works is that the content is built for rewatch. Twerking clips, especially from a back-facing angle like this, are simple, fast, and instantly understood by the viewer. There is no setup needed. No explanation. No context. Just motion, attention, and curiosity. People replay it, send it, comment on whether she is real, and that creates the exact kind of engagement these pages live on. The catch, as always, is retention. A clip like this can bring in the spike, but the money only stays if the character keeps posting and keeps feeling consistent. That is why the smarter operators lock the identity, keep the same hair, same body language, same style, and turn one good-performing angle into a repeatable system. One AI girl, one signature dance style, and one content loop that turns short clips into about $6.8K a month.

Rimi

15,166 次观看 • 2 个月前

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
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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, 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 次观看 • 4 个月前

A 27-year-old from China made $150,000 after finding the real bottleneck behind AI model accounts. It was not generating another face. It was producing enough content to keep the face alive. Most AI girls look convincing in one image, then disappear because the owner cannot make enough Reels, TikToks and Shorts to keep feeding the account. The audience moves on before the paid profile has enough traffic to work. He solved that with a simple production loop. One image of the AI model goes into the system. Motion and dance templates turn it into short videos. The same character can appear in dozens of new clips without filming, scheduling shoots or rebuilding the face every time. That made mass posting possible. The clips generated organic attention, while the profile link moved interested viewers into paid subscriptions and affiliate offers. Most people think the opportunity is creating prettier AI girls. He made $150,000 by solving what happens after the first image is finished.
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A 27-year-old from China made $150,000 after finding the real bottleneck behind AI model accounts. It was not generating another face. It was producing enough content to keep the face alive. Most AI girls look convincing in one image, then disappear because the owner cannot make enough Reels, TikToks and Shorts to keep feeding the account. The audience moves on before the paid profile has enough traffic to work. He solved that with a simple production loop. One image of the AI model goes into the system. Motion and dance templates turn it into short videos. The same character can appear in dozens of new clips without filming, scheduling shoots or rebuilding the face every time. That made mass posting possible. The clips generated organic attention, while the profile link moved interested viewers into paid subscriptions and affiliate offers. Most people think the opportunity is creating prettier AI girls. He made $150,000 by solving what happens after the first image is finished.

Kiyoro

19,807 次观看 • 3 个月前

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

26,237 次观看 • 5 个月前

THIS DEVELOPER OPENED HERMES ON A LAPTOP, SPENT $0 ON API SETUP, SAVED 7 WORKFLOWS, AND CUT 2-HOUR CLIENT TASKS DOWN TO 14 MINUTES he is not giving a polished demo. he is just filming the laptop while Hermes runs, and that is why the clip works. you can see the terminal, the workspace, the task history, and the moment a normal chat tool starts looking like a local operating layer most people still run AI like a vending machine: 1 prompt, 1 answer, 1 reset. Hermes is different. after 5-10 repeated jobs, the useful steps start living inside skills instead of getting rewritten every morning the money math is where it gets ugly. $20 for Claude, $40-90 in API usage, $50 for wrappers, $29 for automation tools, and you are already near $140-190/month before you even sell the first report he used the same flow for 9 small research tasks: 18 competitor pages, 126 review snippets, 9 pricing checks, 9 summary drafts. the first one took 43 minutes. later runs were mostly review, edit, send that is the part people miss about Hermes. it is not trying to win the prettiest chatbot contest. it is trying to make repeated work stop leaking out of the machine every time the session ends
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THIS DEVELOPER OPENED HERMES ON A LAPTOP, SPENT $0 ON API SETUP, SAVED 7 WORKFLOWS, AND CUT 2-HOUR CLIENT TASKS DOWN TO 14 MINUTES he is not giving a polished demo. he is just filming the laptop while Hermes runs, and that is why the clip works. you can see the terminal, the workspace, the task history, and the moment a normal chat tool starts looking like a local operating layer most people still run AI like a vending machine: 1 prompt, 1 answer, 1 reset. Hermes is different. after 5-10 repeated jobs, the useful steps start living inside skills instead of getting rewritten every morning the money math is where it gets ugly. $20 for Claude, $40-90 in API usage, $50 for wrappers, $29 for automation tools, and you are already near $140-190/month before you even sell the first report he used the same flow for 9 small research tasks: 18 competitor pages, 126 review snippets, 9 pricing checks, 9 summary drafts. the first one took 43 minutes. later runs were mostly review, edit, send that is the part people miss about Hermes. it is not trying to win the prettiest chatbot contest. it is trying to make repeated work stop leaking out of the machine every time the session ends

Gipp 🦅

14,593 次观看 • 5 个月前