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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 endsshow more

Gipp 🦅

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14,544 views • 20 days ago •via X (Twitter)

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A 17-year-old student spent $4,200 on 7 Mac minis. Small silver boxes. Stacked on a desk. Connected in one room. From the outside, it looked like a stupid purchase. But inside, it wasn't just 7 computers. It was Skills. Hooks. Memory. Worktrees. One machine handled repeatable tasks. One ran checks automatically. One kept context between sessions. Others ran parallel jobs without touching each other's work. While most people were still typing the same instructions again and again, his setup was already moving. A lot of people pay $200 a month for Claude and still use maybe 20% of it. He built a system around it. Skills turned repeated work into reusable workflows. Hooks made actions fire automatically. Memory stopped every session from starting at zero. Worktrees let multiple tasks run at the same time without collisions. That changed everything. Setup time: under 1 hour once. Time returned: 3 to 5 hours every day. He spent $4,200 once. He made $16,000 in the first week. Not because he found a secret tool. Not because he wrote magical prompts. Because he stopped using it like a chatbot and started using it like infrastructure. 7 Mac minis. 1 student. $4,200 in. $16,000 out. And most people would still call it just a stack of computers.

A 17-year-old student spent $4,200 on 7 Mac minis. Small silver boxes. Stacked on a desk. Connected in one room. From the outside, it looked like a stupid purchase. But inside, it wasn't just 7 computers. It was Skills. Hooks. Memory. Worktrees. One machine handled repeatable tasks. One ran checks automatically. One kept context between sessions. Others ran parallel jobs without touching each other's work. While most people were still typing the same instructions again and again, his setup was already moving. A lot of people pay $200 a month for Claude and still use maybe 20% of it. He built a system around it. Skills turned repeated work into reusable workflows. Hooks made actions fire automatically. Memory stopped every session from starting at zero. Worktrees let multiple tasks run at the same time without collisions. That changed everything. Setup time: under 1 hour once. Time returned: 3 to 5 hours every day. He spent $4,200 once. He made $16,000 in the first week. Not because he found a secret tool. Not because he wrote magical prompts. Because he stopped using it like a chatbot and started using it like infrastructure. 7 Mac minis. 1 student. $4,200 in. $16,000 out. And most people would still call it just a stack of computers.

Gipp 🦅

21,269 views • 2 months ago

I found this last night and I have not stopped thinking about it. HERMES JUST LAUNCHED HERMES DESKTOP. 100% FREE. It is a free desktop app that gives Hermes Agent a proper interface. One place for everything. What is inside: ↳ Auto install and setup, no terminal needed ↳ Streaming chat with token tracking ↳ Multiple agent profiles ↳ Memory you can actually see and edit ↳ 14 tool categories including web, browser, image gen, and voice ↳ Scheduler for automated tasks ↳ 16 messaging gateways including Telegram, WhatsApp, Discord, Slack, and Signal ↳ Full conversation history with search ↳ Backups and logs in one settings screen Works with Anthropic, OpenAI, Gemini, Grok, Groq, Ollama, and more. Hermes Agent is the brain. Hermes Desktop is the cockpit. Free. Open source. Mac, Windows, and Linux.

I found this last night and I have not stopped thinking about it. HERMES JUST LAUNCHED HERMES DESKTOP. 100% FREE. It is a free desktop app that gives Hermes Agent a proper interface. One place for everything. What is inside: ↳ Auto install and setup, no terminal needed ↳ Streaming chat with token tracking ↳ Multiple agent profiles ↳ Memory you can actually see and edit ↳ 14 tool categories including web, browser, image gen, and voice ↳ Scheduler for automated tasks ↳ 16 messaging gateways including Telegram, WhatsApp, Discord, Slack, and Signal ↳ Full conversation history with search ↳ Backups and logs in one settings screen Works with Anthropic, OpenAI, Gemini, Grok, Groq, Ollama, and more. Hermes Agent is the brain. Hermes Desktop is the cockpit. Free. Open source. Mac, Windows, and Linux.

Kanika

59,580 views • 28 days ago

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.

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

540,018 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

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 • 29 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.

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 🦅

1,751,351 views • 1 day ago

I built a 1-click deploy for Hermes Agent No terminal, no Docker, no API keys. In one click it: → Spins up a dedicated cloud container → Configures Hermes with persistent memory & 70+ skills → Connects it to your Telegram bot → Goes live in under 60 seconds Your own AI agent that learns, creates skills, and gets smarter the longer it runs. Reply "HERMES" + RT and I'll send you the link (must be following so I can DM)

I built a 1-click deploy for Hermes Agent No terminal, no Docker, no API keys. In one click it: → Spins up a dedicated cloud container → Configures Hermes with persistent memory & 70+ skills → Connects it to your Telegram bot → Goes live in under 60 seconds Your own AI agent that learns, creates skills, and gets smarter the longer it runs. Reply "HERMES" + RT and I'll send you the link (must be following so I can DM)

Chris

34,473 views • 2 months ago

BlackRock manages $10 trillion. This wallet on Polymarket manages $50K and makes $100K/month with a strategy their quant team would laugh at. He looks at crypto markets on Polymarket, picks price levels where the outcome is already 70-90% likely, buys Yes shares for 70-90 cents and waits. When the outcome hits, the share resolves to $1. He keeps the difference. 20-30 cents profit per trade sounds like nothing. Until you do it 14,878 times His profile: No models. Just RSI, a trendline, and basic momentum. The same boring thing repeated thousands of times. BlackRock has 20,000 employees and offices in 30 countries. This guy has a laptop. The difference is BlackRock needs to be smart. He just needs to be right about things that are already obvious. Most people on Polymarket are trying to predict the future. He is not predicting anything. He is collecting what the present already owes him. Would you rather mass hire PhDs to find alpha, or buy what is already in front of everyone and just do it more than anyone else?

Blaze

20,215 views • 4 months ago

A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage

A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage

Gipp 🦅

191,529 views • 14 days ago

🚨Tom and Jerry cost $50,000 per episode in 1945 that runs near $870,000 today a 19-year-old spent $124 last month and made $12,345 > Claude writes each scene: 10 minutes > Midjourney draws every frame: 20 minutes > Runway animates the chase: 15 minutes > ElevenLabs voices the cast: 10 minutes > Suno scores the gag: 5 minutes > Make uploads it: 0 minutes $870,000 then. $124 now. same chase. he runs it from one laptop. every step is in the article above👇

🚨Tom and Jerry cost $50,000 per episode in 1945 that runs near $870,000 today a 19-year-old spent $124 last month and made $12,345 > Claude writes each scene: 10 minutes > Midjourney draws every frame: 20 minutes > Runway animates the chase: 15 minutes > ElevenLabs voices the cast: 10 minutes > Suno scores the gag: 5 minutes > Make uploads it: 0 minutes $870,000 then. $124 now. same chase. he runs it from one laptop. every step is in the article above👇

Fokki

504,422 views • 10 days ago

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.

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 🦅

590,100 views • 1 month ago

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Google Translate is cooked after this. A developer built a local AI translation engine that runs 40 languages entirely on your own laptop. It's called LibreTranslate. No API key. No usage limits. No sending your documents to Google's servers. You install it once. It runs forever. Here's what it handles: → Paste text. Translated instantly. → Drop in a file. Outputs the translated version. → Point it at a URL. Returns the page in your language. → Build it into your own app via its local REST API. The speed is not the story. The privacy is. Google Translate reads every sentence you paste into it. Legal contracts. Medical records. Internal emails. Client documents. Every word goes to their servers and stays there. LibreTranslate runs entirely offline. Nothing leaves your machine. Ever. The numbers: → 40 languages supported → Runs on CPU -- no GPU needed → Self-hosted in under 5 minutes → REST API built in for developers → 10K+ stars on GitHub 100% open source. MIT licensed. Price: $0. Google charges nothing for Translate either but it charges you something else. GitHub:

Rimsha Bhardwaj

88,314 views • 12 days ago

Europe is quietly becoming what the United States once promised the world. More and more people are looking at their best years ahead and choosing a place where everyday life is designed to work. Where the future feels stable enough to plan for. Where safety is not a luxury product. Where you can build a good life without gambling your health, your family, or your dignity on one bad month. In much of Europe, the “dream” is not about becoming a billionaire. It is about becoming unafraid. It is the freedom of walking home at night without scanning every shadow. The comfort of knowing that if you get sick, you do not need to calculate whether you can afford to be treated. The relief of having a society that still believes children should carry backpacks, not trauma, and definitely not weapons. The calm of streets built for human beings, not just cars. The ability to take a holiday without feeling like you are committing career suicide. The basic decency of labor protections that assume you are a person first and a resource second. And then there is the part people underestimate until they live it: the texture of life. The cities are older and more beautiful than you expect. The distances are smaller. Weekends are real. Food is real. Public spaces are not just decorative, they are functional. Parks are full. Cafes are full. Trains take you somewhere, often across borders, without turning travel into a stress test. You can live in one country, work with another, and visit a third like it is normal because, in many places, it is. The European dream is also a quiet confidence in the social contract. That if you contribute, the system does not abandon you. That you can raise a family without feeling like you are one accident away from ruin. That “getting ahead” does not require burning out. That a good society is one where normal people can live normal lives and still feel proud of them. This is why more and more Americans are not just visiting Europe, but staying. Some come for studies and never leave. Some arrive for a job and realise the lifestyle is the real promotion. Some originally planned a one year experiment and then cannot imagine going back to a place where stress is treated as a personality trait and insecurity is marketed as freedom. Europe is not perfect. It has bureaucracy. It has politics. It has problems that deserve criticism. But in many European countries, life is still built around a simple idea: society should reduce fear, not monetise it. That is the new dream. And people can feel it the moment they arrive. If you could choose one thing to trade for a better life, what would it be: more income, or more security? And what do you think your country would have to change for people to stop leaving, and start staying? Stay connected, Follow Gandalv Gandalv

Europe is quietly becoming what the United States once promised the world. More and more people are looking at their best years ahead and choosing a place where everyday life is designed to work. Where the future feels stable enough to plan for. Where safety is not a luxury product. Where you can build a good life without gambling your health, your family, or your dignity on one bad month. In much of Europe, the “dream” is not about becoming a billionaire. It is about becoming unafraid. It is the freedom of walking home at night without scanning every shadow. The comfort of knowing that if you get sick, you do not need to calculate whether you can afford to be treated. The relief of having a society that still believes children should carry backpacks, not trauma, and definitely not weapons. The calm of streets built for human beings, not just cars. The ability to take a holiday without feeling like you are committing career suicide. The basic decency of labor protections that assume you are a person first and a resource second. And then there is the part people underestimate until they live it: the texture of life. The cities are older and more beautiful than you expect. The distances are smaller. Weekends are real. Food is real. Public spaces are not just decorative, they are functional. Parks are full. Cafes are full. Trains take you somewhere, often across borders, without turning travel into a stress test. You can live in one country, work with another, and visit a third like it is normal because, in many places, it is. The European dream is also a quiet confidence in the social contract. That if you contribute, the system does not abandon you. That you can raise a family without feeling like you are one accident away from ruin. That “getting ahead” does not require burning out. That a good society is one where normal people can live normal lives and still feel proud of them. This is why more and more Americans are not just visiting Europe, but staying. Some come for studies and never leave. Some arrive for a job and realise the lifestyle is the real promotion. Some originally planned a one year experiment and then cannot imagine going back to a place where stress is treated as a personality trait and insecurity is marketed as freedom. Europe is not perfect. It has bureaucracy. It has politics. It has problems that deserve criticism. But in many European countries, life is still built around a simple idea: society should reduce fear, not monetise it. That is the new dream. And people can feel it the moment they arrive. If you could choose one thing to trade for a better life, what would it be: more income, or more security? And what do you think your country would have to change for people to stop leaving, and start staying? Stay connected, Follow Gandalv Gandalv

Gandalv

988,817 views • 3 months ago

This Chinese developer launched Llama 70B locally on a MacBook on a plane and for a full 11 hours without internet ran client projects. He was sitting by the window on a transatlantic flight with a MacBook Pro M4 with 64 GB of memory. WiFi on board cost $25 for the flight. He declined. No cloud API, no connection to Anthropic or OpenAI servers, no internet at all. Just a local Llama 3.3 70B on bf16 and his own orchestrator script. The model runs through llama.cpp. Generation speed, 71 tokens per second. Context around 60,000 tokens. Memory usage, 48.6 GiB out of 64. Battery at takeoff, 3 hours 21 minutes. And he gave the orchestrator this system prompt before takeoff: "You are an offline orchestrator running on a single MacBook. There is no network. The only resources you have are local files in /Users/dev/work, the Llama 70B inference server at localhost:8080, and a battery budget of 3 hours 21 minutes. Process the queue at /Users/dev/work/queue.jsonl (one client task per line). For each task: draft → run local evals → save artefact to /Users/dev/work/done/. Save context checkpoints every 12 tasks so you can resume after a battery swap. Stop only on empty queue or when battery drops below 5%." So the system knows exactly what resources it is running on. It knows it has no connection to the outside world for the next 11 hours. It knows it has finite memory and a finite battery. It knows the human will not intervene until the plane lands. The system runs in 1 loop. Takes a task from the queue, runs it through inference, saves the artifact, writes a checkpoint. Task after task, just like that. And only when the battery drops below 5% does the orchestrator automatically pause, waits for the laptop to switch to the backup power bank, and continues from the last checkpoint. Here is what the system actually writes in his log during the flight: "saved context checkpoint 8 of 12 (pos_min = 488, pos_max = 50118, size = 62.813 MiB)" "restored context checkpoint (pos_min = 488, pos_max = 50118)" "prompt processing progress: n_tokens = 50 / 60 818" "task 37016 done | tps = 71 s tokens text → /Users/dev/work/done/proposal_westside.md" Outside the window, clouds, blue sky, and no WiFi. On the tray, 1 MacBook, an open terminal on 2 screens, and an inference server on localhost. From what I have observed, this is the cleanest offline AI workflow I have seen in the past year: 11 hours of flight, $0 for WiFi, and the entire client queue closed before landing.

This Chinese developer launched Llama 70B locally on a MacBook on a plane and for a full 11 hours without internet ran client projects. He was sitting by the window on a transatlantic flight with a MacBook Pro M4 with 64 GB of memory. WiFi on board cost $25 for the flight. He declined. No cloud API, no connection to Anthropic or OpenAI servers, no internet at all. Just a local Llama 3.3 70B on bf16 and his own orchestrator script. The model runs through llama.cpp. Generation speed, 71 tokens per second. Context around 60,000 tokens. Memory usage, 48.6 GiB out of 64. Battery at takeoff, 3 hours 21 minutes. And he gave the orchestrator this system prompt before takeoff: "You are an offline orchestrator running on a single MacBook. There is no network. The only resources you have are local files in /Users/dev/work, the Llama 70B inference server at localhost:8080, and a battery budget of 3 hours 21 minutes. Process the queue at /Users/dev/work/queue.jsonl (one client task per line). For each task: draft → run local evals → save artefact to /Users/dev/work/done/. Save context checkpoints every 12 tasks so you can resume after a battery swap. Stop only on empty queue or when battery drops below 5%." So the system knows exactly what resources it is running on. It knows it has no connection to the outside world for the next 11 hours. It knows it has finite memory and a finite battery. It knows the human will not intervene until the plane lands. The system runs in 1 loop. Takes a task from the queue, runs it through inference, saves the artifact, writes a checkpoint. Task after task, just like that. And only when the battery drops below 5% does the orchestrator automatically pause, waits for the laptop to switch to the backup power bank, and continues from the last checkpoint. Here is what the system actually writes in his log during the flight: "saved context checkpoint 8 of 12 (pos_min = 488, pos_max = 50118, size = 62.813 MiB)" "restored context checkpoint (pos_min = 488, pos_max = 50118)" "prompt processing progress: n_tokens = 50 / 60 818" "task 37016 done | tps = 71 s tokens text → /Users/dev/work/done/proposal_westside.md" Outside the window, clouds, blue sky, and no WiFi. On the tray, 1 MacBook, an open terminal on 2 screens, and an inference server on localhost. From what I have observed, this is the cleanest offline AI workflow I have seen in the past year: 11 hours of flight, $0 for WiFi, and the entire client queue closed before landing.

Blaze

1,837,412 views • 1 month ago

The largest theft in history has already happened. The people behind it just cannot open what they stole yet. Right now, intelligence agencies and criminal groups are quietly copying the world's encrypted data, bank records, medical files, state secrets, private messages, and storing every byte untouched. They cannot read any of it. They are collecting it anyway, because they know the key is about to be invented. The strategy has a name, harvest now, decrypt later, and in 2026 it stopped being theory. Washington declared this the Year of Quantum Security in January, backed by the FBI, the NSA, and NIST. Canada ordered every federal agency to file a migration plan by April. Europe set its deadline for December. Governments do not impose operational deadlines on a someday problem. They do it when the clock is already running. Here is what moved the clock. Every password, every transfer, every secret on Earth is protected by one assumption, that a certain math problem is too hard to solve. Quantum computers solve exactly that problem. For years the machine that could do it looked decades away. Then in late 2025 Google's Willow chip cracked the hardest part of building one, and in March 2026 Google's own researchers estimated that breaking the encryption behind Bitcoin might take fewer than 500,000 qubits, down from 20 million, and could run in minutes. The day this becomes real has a name, Q-Day, and the latest estimates place it between 2030 and 2033. Now make it concrete. Roughly 6.5 million Bitcoin, about a third of every coin that will ever exist, worth close to 500 billion dollars, sit in addresses that have already exposed the very key a quantum computer needs. That includes the coins of Satoshi, the anonymous creator. On Q-Day they become, in the researchers' own word, trivially stealable. It would not look like a crash or a whale selling. It would look like half a trillion dollars of the most secure money ever built simply walking out the door. The asset designed to trust no one and no institution turns out to rest on a single unverified bet, that one math problem stays hard forever. This is what sits beneath the entire digital world. A bank balance, a Bitcoin, a classified cable, all of it is real only because of a proof you supposedly cannot forge. Quantum breaks the proof. Everything we call secure is true only until someone finally checks, and for the first time the check is visible on the horizon. You cannot know whether your data has already been copied. You cannot know the exact day the key arrives. The trust holding up the digital age is a clock counting down to a zero no one can see. The honest counter matters. No machine on Earth can break this encryption today, and serious cryptographers still argue the real threat is a decade or more away. The timeline is far from certain. Quantum-safe codes already exist, the migration has started, and Bitcoin can move its coins to safety before Q-Day if it acts in time. The danger is not that everything breaks tomorrow. It is that anything which must stay secret into the 2030s, a state secret, an identity, a private key, is being stolen today and is already on the clock. The breach is not coming. It is already here, sitting in storage, perfectly encrypted, waiting for a machine that does not exist yet to read it out loud. Research and opinion, not investment advice.

The largest theft in history has already happened. The people behind it just cannot open what they stole yet. Right now, intelligence agencies and criminal groups are quietly copying the world's encrypted data, bank records, medical files, state secrets, private messages, and storing every byte untouched. They cannot read any of it. They are collecting it anyway, because they know the key is about to be invented. The strategy has a name, harvest now, decrypt later, and in 2026 it stopped being theory. Washington declared this the Year of Quantum Security in January, backed by the FBI, the NSA, and NIST. Canada ordered every federal agency to file a migration plan by April. Europe set its deadline for December. Governments do not impose operational deadlines on a someday problem. They do it when the clock is already running. Here is what moved the clock. Every password, every transfer, every secret on Earth is protected by one assumption, that a certain math problem is too hard to solve. Quantum computers solve exactly that problem. For years the machine that could do it looked decades away. Then in late 2025 Google's Willow chip cracked the hardest part of building one, and in March 2026 Google's own researchers estimated that breaking the encryption behind Bitcoin might take fewer than 500,000 qubits, down from 20 million, and could run in minutes. The day this becomes real has a name, Q-Day, and the latest estimates place it between 2030 and 2033. Now make it concrete. Roughly 6.5 million Bitcoin, about a third of every coin that will ever exist, worth close to 500 billion dollars, sit in addresses that have already exposed the very key a quantum computer needs. That includes the coins of Satoshi, the anonymous creator. On Q-Day they become, in the researchers' own word, trivially stealable. It would not look like a crash or a whale selling. It would look like half a trillion dollars of the most secure money ever built simply walking out the door. The asset designed to trust no one and no institution turns out to rest on a single unverified bet, that one math problem stays hard forever. This is what sits beneath the entire digital world. A bank balance, a Bitcoin, a classified cable, all of it is real only because of a proof you supposedly cannot forge. Quantum breaks the proof. Everything we call secure is true only until someone finally checks, and for the first time the check is visible on the horizon. You cannot know whether your data has already been copied. You cannot know the exact day the key arrives. The trust holding up the digital age is a clock counting down to a zero no one can see. The honest counter matters. No machine on Earth can break this encryption today, and serious cryptographers still argue the real threat is a decade or more away. The timeline is far from certain. Quantum-safe codes already exist, the migration has started, and Bitcoin can move its coins to safety before Q-Day if it acts in time. The danger is not that everything breaks tomorrow. It is that anything which must stay secret into the 2030s, a state secret, an identity, a private key, is being stolen today and is already on the clock. The breach is not coming. It is already here, sitting in storage, perfectly encrypted, waiting for a machine that does not exist yet to read it out loud. Research and opinion, not investment advice.

Shanaka Anslem Perera ⚡

180,249 views • 2 days ago

If you use Hermes agent, you need to save this resource. Nous Research has an official Hermes Skills Hub with hundreds of Hermes Skills. Skills for creative work, developer tools, research, and more. Search the marketplace here:

If you use Hermes agent, you need to save this resource. Nous Research has an official Hermes Skills Hub with hundreds of Hermes Skills. Skills for creative work, developer tools, research, and more. Search the marketplace here:

AI Edge

40,257 views • 27 days ago

Is Michael Saylor about to get a margin call? No. And the reason is more interesting than the rumor, because what he built instead may be harder to escape than one. A margin call needs a lender who can seize collateral when the price drops. Strategy has none. Its $6.7 billion in debt is convertible notes, the largest tranche due in 2029, with no loan-to-value trigger and no clause that lets anyone take a coin because Bitcoin fell. Saylor learned that in 2022, when he did have a collateralized loan and sweated a liquidation price, then rebuilt the structure so it could never happen again. On the literal question he is right, and the people calling for his liquidation this week do not understand what they see. But killing the fast death created a slow one almost nobody is pricing. To fund his buying, Saylor issued a mountain of perpetual preferred stock that pays a fixed dividend forever, near 11.5 percent, no matter where Bitcoin trades. That annual bill quadrupled from about $300 million in January to roughly $1.2 billion now, while the cash reserve that pays it fell 38 percent this year to near $1.4 billion, after the company spent $1.5 billion in May retiring debt. Put those two numbers together and you get the figure that actually matters, and it is not a Bitcoin price. It is a countdown. Dividend coverage, the time the cash can keep paying that bill, has collapsed from more than seven years in early 2026 to between ten and fourteen months, depending on whose math you use. Months, not years. The market is already pricing it, just not where the rumor is looking. That preferred stock is engineered to sit at $100. Last week it cracked to $82.50, a record 17.5 percent below par. That discount is investors quietly clocking the strain while the timeline screams about a margin call that cannot happen. There is a clean way out, and it is the one door the structure was built to keep shut. Restoring a safe two years of coverage takes about $2.8 billion, roughly double what Strategy holds, and the fastest path there is to sell Bitcoin. But selling crystallizes a $10.6 billion loss, breaks the never-sell promise that gives the stock its premium, and bleeds the very asset the machine exists to hoard. The exit and the wound are the same cut. He already brushed it, selling 32 coins on June 1 to cover a payment. Thirty-two against more than 847,000 is a rounding error in size and an earthquake in meaning, because the company that swore it would never sell, sold, to pay a dividend. And there is a second trigger almost no one has read, buried in the fine print. If Saylor ever simply skips a preferred payment to save cash, the missed amount compounds, the senior layer can ratchet its rate higher, a senior miss freezes payments to every junior layer beneath it, and after enough missed quarters those preferred holders can start taking board seats. No one seizes a coin. But control begins migrating to the people he owes. The clock does not just run down. It hands away the keys at the end. So the honest verdict is the one neither side is shouting. There is no margin call and no imminent bankruptcy. The structure protects him exactly as designed. What it cannot protect him from is a fixed bill that grows while the cash shrinks, where every exit deepens the hole. Sell Bitcoin and break the story. Issue stock into a price near its lowest since 2024 and punish your holders. Skip the dividend and start losing the company by the boardroom. Saylor did not escape the margin call. He traded a cliff for a clock. A cliff takes you in an afternoon and a stranger pulls the trigger. This clock takes months, and at the end the trigger is pulled by the only two forces he swore would never touch it, his own hand, or the people he owes. The rumor asks whether someone is about to call his loan. The real question is how many months he can keep paying before he has to sell the dream, dilute the believers, or hand over the board to keep the lights on.

Is Michael Saylor about to get a margin call? No. And the reason is more interesting than the rumor, because what he built instead may be harder to escape than one. A margin call needs a lender who can seize collateral when the price drops. Strategy has none. Its $6.7 billion in debt is convertible notes, the largest tranche due in 2029, with no loan-to-value trigger and no clause that lets anyone take a coin because Bitcoin fell. Saylor learned that in 2022, when he did have a collateralized loan and sweated a liquidation price, then rebuilt the structure so it could never happen again. On the literal question he is right, and the people calling for his liquidation this week do not understand what they see. But killing the fast death created a slow one almost nobody is pricing. To fund his buying, Saylor issued a mountain of perpetual preferred stock that pays a fixed dividend forever, near 11.5 percent, no matter where Bitcoin trades. That annual bill quadrupled from about $300 million in January to roughly $1.2 billion now, while the cash reserve that pays it fell 38 percent this year to near $1.4 billion, after the company spent $1.5 billion in May retiring debt. Put those two numbers together and you get the figure that actually matters, and it is not a Bitcoin price. It is a countdown. Dividend coverage, the time the cash can keep paying that bill, has collapsed from more than seven years in early 2026 to between ten and fourteen months, depending on whose math you use. Months, not years. The market is already pricing it, just not where the rumor is looking. That preferred stock is engineered to sit at $100. Last week it cracked to $82.50, a record 17.5 percent below par. That discount is investors quietly clocking the strain while the timeline screams about a margin call that cannot happen. There is a clean way out, and it is the one door the structure was built to keep shut. Restoring a safe two years of coverage takes about $2.8 billion, roughly double what Strategy holds, and the fastest path there is to sell Bitcoin. But selling crystallizes a $10.6 billion loss, breaks the never-sell promise that gives the stock its premium, and bleeds the very asset the machine exists to hoard. The exit and the wound are the same cut. He already brushed it, selling 32 coins on June 1 to cover a payment. Thirty-two against more than 847,000 is a rounding error in size and an earthquake in meaning, because the company that swore it would never sell, sold, to pay a dividend. And there is a second trigger almost no one has read, buried in the fine print. If Saylor ever simply skips a preferred payment to save cash, the missed amount compounds, the senior layer can ratchet its rate higher, a senior miss freezes payments to every junior layer beneath it, and after enough missed quarters those preferred holders can start taking board seats. No one seizes a coin. But control begins migrating to the people he owes. The clock does not just run down. It hands away the keys at the end. So the honest verdict is the one neither side is shouting. There is no margin call and no imminent bankruptcy. The structure protects him exactly as designed. What it cannot protect him from is a fixed bill that grows while the cash shrinks, where every exit deepens the hole. Sell Bitcoin and break the story. Issue stock into a price near its lowest since 2024 and punish your holders. Skip the dividend and start losing the company by the boardroom. Saylor did not escape the margin call. He traded a cliff for a clock. A cliff takes you in an afternoon and a stranger pulls the trigger. This clock takes months, and at the end the trigger is pulled by the only two forces he swore would never touch it, his own hand, or the people he owes. The rumor asks whether someone is about to call his loan. The real question is how many months he can keep paying before he has to sell the dream, dilute the believers, or hand over the board to keep the lights on.

Shanaka Anslem Perera ⚡

52,134 views • 3 days ago

This 47-year-old man from Japan made $14,450 in a month by creating an AI girl and turning her into a virtual influencer. He got tired of watching people hire a model and a photographer and an editor and a content manager for a virtual influencer and burn a budget on it. He built an AI girl from scratch and handed the whole operation to Claude. A project like that used to cost a team. His entire spend is $20 a month. No model. No studio. No team. Here is the exact breakdown: → First he built the persona herself: a face, a character, a backstory and a manner that the AI keeps identical in every clip → He films it simply: the girl is on top of the frame and he sits below in the same room and she repeats his moves and his face so the character reads as alive → The first free source is TikTok and the second is Reddit with photos and short videos and behind-the-scenes and both point to one link in the profile → From there Claude carries it all: it designs the visuals and writes the captions and shapes the content for the algorithm and posts on a schedule almost without him → From that link a person lands not on a pretty picture but on a subscription, a digital product or a private community The move that 96% skip: they polish the girl herself but the asset is not the face, it is the system around her. Make just a pretty AI girl and she dissolves into thousands like her within a week. Run two free traffic streams into her and a stack of ways to pay and the attention starts turning into money because people pay not for a picture but for access and a product and exclusivity. Here is what those $14,450 are made of. A private Patreon subscription: 700 people at $9.90 is $6,930. Digital products on Gumroad like photosets and wallpapers and prompt packs: 300 sales at $19 is $5,700. Affiliate offers for AI tools: 100 conversions at $12 is $1,200. Donations and paid requests added about $620 more. He grew the TikTok in 5 days: the clips pulled 1,500,000 views and 6,790 followers off a persona that did not exist a week earlier. Under the clips people argue whether the girl is real and that argument carries them further on its own. Not a single shoot day. Not a dollar on ads. Not a single hire. Just one AI persona. Two free traffic streams. And the discipline to build a system around her not just polish one picture. Half of you are already typing that nobody will watch a virtual influencer. The other half is already setting up an account for their first persona. Which half are you in?

Kaidu

48,471 views • 13 days ago

The clinical term is malignant narcissism. There is a specific kind of man who walks into a room and immediately begins rearranging it. Not the furniture. The people. By minute four, he has forgotten the names of half of them. That is not a flaw in the system. That is the system. The clinical term is malignant narcissism. It sits at the intersection of four things: narcissistic personality disorder, antisocial features, paranoia, and sadism. The sadism part is what people miss. He does not simply lack empathy. He has inverted it. He reads your emotional state with the precision of a surgeon, then uses that information like a scalpel. Maximum discomfort. Minimum legal risk. Otto Kernberg, the psychiatrist who formalized the concept, called it one of the most dangerous personality structures a human being can carry. Not because it is loud. Because it is effective. And because it is almost impossible to name while you are standing inside it. History keeps producing the same man. Robert Maxwell looted his employees’ pension funds while they trusted him completely. Hundreds of millions. He knew the whole time. There is no evidence he experienced this as a problem. Silvio Berlusconi governed Italy like a man who had confused the country with his personal property. Laws bent to fit his legal situation. Courts were hollowed out when they became inconvenient. People who spent time close to him reported the same thing afterward: you left the conversation certain you had agreed to something. You just could not remember what. Charm makes you feel good about yourself. This makes you feel good about him. There is a difference. It takes most people years to locate it. The pattern has a shape. Once you see it you cannot unsee it. It begins with grandiosity so complete it functions as a worldview. Other people exist in one of three categories: instruments, obstacles, or audiences. He is perfectly pleasant to all three, for exactly as long as they remain useful. The moment that changes, so does he. The switch is not gradual. It is a door closing. It continues with a specific relationship to truth. He does not lie the way ordinary people lie, defensively, to avoid consequences. He lies the way a chess player moves pieces. If I can make you accept a false thing, I have demonstrated power over your reality. If you push back, I do not retreat. I escalate. The goal was never the fact. The goal was always the submission. It sustains itself by dismantling anything capable of judgment. Independent courts. A free press. Rival centers of power. These feel to him not like inconveniences but like attacks. The structure that can judge him is the structure that must be broken. This is not calculated. It is reflexive. It is as automatic as flinching. The frightening thing is not that these men exist. The frightening thing is the gap between when the room starts rearranging itself and when anyone names what they are watching. That gap can last years. Decades. Sometimes it outlasts the man entirely, and the next generation inherits the rearranged room and calls it normal. By the time someone says it plainly, the furniture is long gone. And he is already in the next room. Gandalv

The clinical term is malignant narcissism. There is a specific kind of man who walks into a room and immediately begins rearranging it. Not the furniture. The people. By minute four, he has forgotten the names of half of them. That is not a flaw in the system. That is the system. The clinical term is malignant narcissism. It sits at the intersection of four things: narcissistic personality disorder, antisocial features, paranoia, and sadism. The sadism part is what people miss. He does not simply lack empathy. He has inverted it. He reads your emotional state with the precision of a surgeon, then uses that information like a scalpel. Maximum discomfort. Minimum legal risk. Otto Kernberg, the psychiatrist who formalized the concept, called it one of the most dangerous personality structures a human being can carry. Not because it is loud. Because it is effective. And because it is almost impossible to name while you are standing inside it. History keeps producing the same man. Robert Maxwell looted his employees’ pension funds while they trusted him completely. Hundreds of millions. He knew the whole time. There is no evidence he experienced this as a problem. Silvio Berlusconi governed Italy like a man who had confused the country with his personal property. Laws bent to fit his legal situation. Courts were hollowed out when they became inconvenient. People who spent time close to him reported the same thing afterward: you left the conversation certain you had agreed to something. You just could not remember what. Charm makes you feel good about yourself. This makes you feel good about him. There is a difference. It takes most people years to locate it. The pattern has a shape. Once you see it you cannot unsee it. It begins with grandiosity so complete it functions as a worldview. Other people exist in one of three categories: instruments, obstacles, or audiences. He is perfectly pleasant to all three, for exactly as long as they remain useful. The moment that changes, so does he. The switch is not gradual. It is a door closing. It continues with a specific relationship to truth. He does not lie the way ordinary people lie, defensively, to avoid consequences. He lies the way a chess player moves pieces. If I can make you accept a false thing, I have demonstrated power over your reality. If you push back, I do not retreat. I escalate. The goal was never the fact. The goal was always the submission. It sustains itself by dismantling anything capable of judgment. Independent courts. A free press. Rival centers of power. These feel to him not like inconveniences but like attacks. The structure that can judge him is the structure that must be broken. This is not calculated. It is reflexive. It is as automatic as flinching. The frightening thing is not that these men exist. The frightening thing is the gap between when the room starts rearranging itself and when anyone names what they are watching. That gap can last years. Decades. Sometimes it outlasts the man entirely, and the next generation inherits the rearranged room and calls it normal. By the time someone says it plainly, the furniture is long gone. And he is already in the next room. Gandalv

Gandalv

23,407 views • 3 months ago

Bucks v Pacers Game 1 film thread 🧵 First defensive possession of the game and you can already get a feel for how this is going to go for the Bucks Middle of the floor ball screen from Turner with Brook in drop. Turner pops and Brook gives good effort to get out there and contest the shot. Turner still hits it. To ask Brook to have to give that type of effort every single play and put themselves in that situation every time down the floor is just not a winning game plan.

Bucks v Pacers Game 1 film thread 🧵 First defensive possession of the game and you can already get a feel for how this is going to go for the Bucks Middle of the floor ball screen from Turner with Brook in drop. Turner pops and Brook gives good effort to get out there and contest the shot. Turner still hits it. To ask Brook to have to give that type of effort every single play and put themselves in that situation every time down the floor is just not a winning game plan.

Bucks Breakdown

67,461 views • 1 year ago

Hermes meets SuperGrok! xAI just made every SuperGrok subscription work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.

Akshay 🚀

143,942 views • 1 month ago