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A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault....

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CyrilXBT

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127,456 Aufrufe • vor 22 Tagen •via X (Twitter)

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Obsidian notes = raw material. This system = finished output. Five workflows that process every capture into something usable. Decision support. Writing fuel. Conversation material. Action triggers. Every note connected. Every idea surfaced at the right moment. Nothing captured and forgotten. The vault that produces instead of collects. Read this and Bookmark it now.
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Obsidian notes = raw material. This system = finished output. Five workflows that process every capture into something usable. Decision support. Writing fuel. Conversation material. Action triggers. Every note connected. Every idea surfaced at the right moment. Nothing captured and forgotten. The vault that produces instead of collects. Read this and Bookmark it now.

CyrilXBT

92,572 Aufrufe • vor 1 Monat

THIS IS WHAT YOUR SECOND BRAIN SHOULD LOOK LIKE most people dump notes into obsidian and call it a second brain it’s not a second brain it’s a second drawer karpathy just dropped the pattern that changes this and it’s called the llm wiki every time you add a source ai reads it, extracts key claims, updates every connected note and flags contradictions your obsidian stops being an archive and starts being alive save this and show it to someone still using notion as a second brain full breakdown in the article ↓
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THIS IS WHAT YOUR SECOND BRAIN SHOULD LOOK LIKE most people dump notes into obsidian and call it a second brain it’s not a second brain it’s a second drawer karpathy just dropped the pattern that changes this and it’s called the llm wiki every time you add a source ai reads it, extracts key claims, updates every connected note and flags contradictions your obsidian stops being an archive and starts being alive save this and show it to someone still using notion as a second brain full breakdown in the article ↓

leopardracer

123,618 Aufrufe • vor 18 Tagen

THIS TRADER TRAINED HIS OBSIDIAN VAULT ON HUNDREDS OF CHART PATTERNS AND NOW IT THINKS WITH HIM every setup he ever studied is in there > linked to the outcome > linked to the context > linked to what he was thinking at the time he types one command > Claude Code finds the relevant sources, runs analysis through NotebookLM, saves everything structured the vault doesn't just store information anymore it connects it most traders are still screenshotting charts into a Discord and forgetting them in 48 hours article below
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THIS TRADER TRAINED HIS OBSIDIAN VAULT ON HUNDREDS OF CHART PATTERNS AND NOW IT THINKS WITH HIM every setup he ever studied is in there > linked to the outcome > linked to the context > linked to what he was thinking at the time he types one command > Claude Code finds the relevant sources, runs analysis through NotebookLM, saves everything structured the vault doesn't just store information anymore it connects it most traders are still screenshotting charts into a Discord and forgetting them in 48 hours article below

monokern

81,079 Aufrufe • vor 1 Monat

THIS MAN HASN’T OPENED HIS TASK MANAGER IN A WEEK AND HIS ENTIRE LIFE IS STILL ON TRACK he dumped everything into one folder before bed and closed his laptop woke up to a system that had already sorted every note and flagged every stalled project and assigned every task his coworkers are still living in their inboxes the only difference is one folder called CAPTURE and claude running at 8pm every night every idea goes in and claude files it and nothing requires a decision and nothing gets lost
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THIS MAN HASN’T OPENED HIS TASK MANAGER IN A WEEK AND HIS ENTIRE LIFE IS STILL ON TRACK he dumped everything into one folder before bed and closed his laptop woke up to a system that had already sorted every note and flagged every stalled project and assigned every task his coworkers are still living in their inboxes the only difference is one folder called CAPTURE and claude running at 8pm every night every idea goes in and claude files it and nothing requires a decision and nothing gets lost

leopardracer

312,942 Aufrufe • vor 1 Monat

Obsidian plus Vellum = a second brain that never stops thinking. Works while you sleep. Obsidian holds everything you know. Vellum reasons across it continuously. Every idea connected. Every pattern surfaced. Every insight waiting when you wake up. The people who build this tonight will never go back to thinking alone. Read this and Bookmark it now.
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Obsidian plus Vellum = a second brain that never stops thinking. Works while you sleep. Obsidian holds everything you know. Vellum reasons across it continuously. Every idea connected. Every pattern surfaced. Every insight waiting when you wake up. The people who build this tonight will never go back to thinking alone. Read this and Bookmark it now.

CyrilXBT

253,256 Aufrufe • vor 1 Monat

Realising you have been measuring your note-taking system by how many notes you have when the only metric that actually matters is how many times a note contributed to a decision, a piece of writing, or an action. Most notes in Obsidian never get used. Not because the information was not valuable. Because every note-taking system optimises for capturing and ignores using entirely. Someone built a five-workflow Obsidian system designed from the opposite end. The contribution rate compounds from the first processed note. Here is the full build nobody is talking about.
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Realising you have been measuring your note-taking system by how many notes you have when the only metric that actually matters is how many times a note contributed to a decision, a piece of writing, or an action. Most notes in Obsidian never get used. Not because the information was not valuable. Because every note-taking system optimises for capturing and ignores using entirely. Someone built a five-workflow Obsidian system designed from the opposite end. The contribution rate compounds from the first processed note. Here is the full build nobody is talking about.

Dami-Defi

30,930 Aufrufe • vor 1 Monat

Andrej Karpathy, the CEO of Obsidian, and Claude Code just built the smartest second brain on earth. It started with a 1-page gist that 21M people read. Karpathy frame flips everything you know about notes: Obsidian is the IDE, Claude Code is the programmer, and your notes are the codebase. You don’t ask AI questions it forgets by tomorrow you make it maintain a living wiki. 3 commands run the whole system. Ingest: drop an article, a podcast, a PDF, and Claude splits it into atomic pages linked to everything you already know. Query: ask anything and it answers from your own notes, in your own words, citing your own pages instead of guessing from training data. Lint: once a week Claude walks the entire vault, flags contradictions, kills stale claims, and wires orphan notes back in. Then Steph Ango made his move. The Obsidian CEO didn’t bolt an “Ask AI” button onto the app he shipped 5 skill files that teach Claude to write Obsidian’s native language: wikilinks, Canvas, Bases, the CLI. The repo crossed 13,900 stars in weeks and sits at 41,000 now. Karpathy runs it on his own reading: 100 articles and 400,000 words, cross-linked and maintained while he sleeps. No vector database, no embeddings, no $20 a month memory app just a folder of plain markdown and an agent that never gets tired of the boring part: the linking, the filing, the upkeep that killed every Zettelkasten since 1965. Your vault has 3,000 notes nobody will ever reopen. His read all of themselves by breakfast. Every app promised a second brain this is the first one that thinks.
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Andrej Karpathy, the CEO of Obsidian, and Claude Code just built the smartest second brain on earth. It started with a 1-page gist that 21M people read. Karpathy frame flips everything you know about notes: Obsidian is the IDE, Claude Code is the programmer, and your notes are the codebase. You don’t ask AI questions it forgets by tomorrow you make it maintain a living wiki. 3 commands run the whole system. Ingest: drop an article, a podcast, a PDF, and Claude splits it into atomic pages linked to everything you already know. Query: ask anything and it answers from your own notes, in your own words, citing your own pages instead of guessing from training data. Lint: once a week Claude walks the entire vault, flags contradictions, kills stale claims, and wires orphan notes back in. Then Steph Ango made his move. The Obsidian CEO didn’t bolt an “Ask AI” button onto the app he shipped 5 skill files that teach Claude to write Obsidian’s native language: wikilinks, Canvas, Bases, the CLI. The repo crossed 13,900 stars in weeks and sits at 41,000 now. Karpathy runs it on his own reading: 100 articles and 400,000 words, cross-linked and maintained while he sleeps. No vector database, no embeddings, no $20 a month memory app just a folder of plain markdown and an agent that never gets tired of the boring part: the linking, the filing, the upkeep that killed every Zettelkasten since 1965. Your vault has 3,000 notes nobody will ever reopen. His read all of themselves by breakfast. Every app promised a second brain this is the first one that thinks.

West Lord

463,758 Aufrufe • vor 2 Tagen

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.
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Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.

West Lord

584,370 Aufrufe • vor 15 Tagen

A 20-year-old student from China, Li Hao, built an AI speed radar with Claude alone and sold it to a city district for $317,000 He wrote the whole thing in 9 days, spending about $20 on Claude API calls He set an old camera on his balcony, pointed it at the intersection below, and let Claude watch the road Claude tags every car, motorbike and pedestrian in real time, 653 in five minutes, and flags anyone over the limit The moment a car speeds, Claude clips the video, reads the license plate, matches the owner, and emails the fine on its own A normal radar takes one photo and misses half the time. Claude records full video, so there is nothing to dispute, and the fines go out with no operator He walked into the district office with a flash drive and asked for 10 minutes. he left with a contract Every Claude config he used is in the article
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A 20-year-old student from China, Li Hao, built an AI speed radar with Claude alone and sold it to a city district for $317,000 He wrote the whole thing in 9 days, spending about $20 on Claude API calls He set an old camera on his balcony, pointed it at the intersection below, and let Claude watch the road Claude tags every car, motorbike and pedestrian in real time, 653 in five minutes, and flags anyone over the limit The moment a car speeds, Claude clips the video, reads the license plate, matches the owner, and emails the fine on its own A normal radar takes one photo and misses half the time. Claude records full video, so there is nothing to dispute, and the fines go out with no operator He walked into the district office with a flash drive and asked for 10 minutes. he left with a contract Every Claude config he used is in the article

Fokki

330,862 Aufrufe • vor 12 Tagen

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

Fokki

12,933 Aufrufe • vor 17 Tagen

THIS GUY HAD 1,283 NOTES AND HIS SYSTEM WAS DUMBER THAN A FOLDER that galaxy in the background is his Obsidian vault > looks incredible > does nothing dead notes, zero connections, zero value extracted from any of it > the fix isn't taking better notes > it's building a pipeline where Claude Opus 4.8 does the research, NotebookLM does the analysis, and every session feeds your vault automatically one command: > Claude Code searches YouTube for 10 relevant sources > passes them to NotebookLM - Google's servers do the heavy processing, not your tokens > NotebookLM runs full analysis, generates infographics, mindmaps, flashcards > everything lands as structured markdown in your Obsidian vault, linked and ready total time: 6 minutes > after a month the vault knows your thinking style. after a year it's a trained research assistant the $300K AI architects aren't taking better notes > they're building systems that compound 30-minute setup. full step-by-step in the article below 👇
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THIS GUY HAD 1,283 NOTES AND HIS SYSTEM WAS DUMBER THAN A FOLDER that galaxy in the background is his Obsidian vault > looks incredible > does nothing dead notes, zero connections, zero value extracted from any of it > the fix isn't taking better notes > it's building a pipeline where Claude Opus 4.8 does the research, NotebookLM does the analysis, and every session feeds your vault automatically one command: > Claude Code searches YouTube for 10 relevant sources > passes them to NotebookLM - Google's servers do the heavy processing, not your tokens > NotebookLM runs full analysis, generates infographics, mindmaps, flashcards > everything lands as structured markdown in your Obsidian vault, linked and ready total time: 6 minutes > after a month the vault knows your thinking style. after a year it's a trained research assistant the $300K AI architects aren't taking better notes > they're building systems that compound 30-minute setup. full step-by-step in the article below 👇

Mr. Buzzoni

48,417 Aufrufe • vor 1 Monat

Most people see a Mac Mini as a home computer. He saw a $300 invoice waiting to happen. A guy in Shenzhen figured out that every early-stage startup, every founder, every small business owner needs the same thing, someone to tell them what their competitors are doing and where the gaps are. Nobody wants to pay $2,000 for a research firm. Nobody wants to wait a week. He set up Hermes on a laptop. Local model. No API costs. First report took 15 minutes. He charged $300 and delivered same day. Then he bought another machine. Then another. Now there are 65 Mac Minis on metal shelves in his apartment. Each one runs its own agent. Each agent has its own skills folder that grows every time it completes a task. Month one: $3,200. Month three: $9,600. The tool: Hermes Agent. Free on GitHub. The model: Qwen 3.6 27B. Also free. Total monthly cost: $2 in electricity. The hardware paid for itself in week two. The shelves haven't changed. He just keeps adding machines.
0:10

Most people see a Mac Mini as a home computer. He saw a $300 invoice waiting to happen. A guy in Shenzhen figured out that every early-stage startup, every founder, every small business owner needs the same thing, someone to tell them what their competitors are doing and where the gaps are. Nobody wants to pay $2,000 for a research firm. Nobody wants to wait a week. He set up Hermes on a laptop. Local model. No API costs. First report took 15 minutes. He charged $300 and delivered same day. Then he bought another machine. Then another. Now there are 65 Mac Minis on metal shelves in his apartment. Each one runs its own agent. Each agent has its own skills folder that grows every time it completes a task. Month one: $3,200. Month three: $9,600. The tool: Hermes Agent. Free on GitHub. The model: Qwen 3.6 27B. Also free. Total monthly cost: $2 in electricity. The hardware paid for itself in week two. The shelves haven't changed. He just keeps adding machines.

Superior

28,895 Aufrufe • vor 1 Monat

People don’t grasp the magnitude of what Lee Know did at the MAMA Awards 2025. He showed why he is considered, not only the best dancer and performer of his generation, but also in the top 5 of all K-pop idols. He performed for more than 10 minutes with such a severe leg injury that makes it impossible for him to walk properly, needing a wheelchair to get around. Even with this, he delivered an outstanding performance, one at the same level of quality as every one of his presentations. It's not only an inspiration, but a pride and joy to stan someone like him. STAYS and Jewels can say with the outmost confidence that they stan an idol that comes once in a lifetime. LEE KNOW LIGHTS UP MAMA #MAMA2025_LEEKNOW
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People don’t grasp the magnitude of what Lee Know did at the MAMA Awards 2025. He showed why he is considered, not only the best dancer and performer of his generation, but also in the top 5 of all K-pop idols. He performed for more than 10 minutes with such a severe leg injury that makes it impossible for him to walk properly, needing a wheelchair to get around. Even with this, he delivered an outstanding performance, one at the same level of quality as every one of his presentations. It's not only an inspiration, but a pride and joy to stan someone like him. STAYS and Jewels can say with the outmost confidence that they stan an idol that comes once in a lifetime. LEE KNOW LIGHTS UP MAMA #MAMA2025_LEEKNOW

LEE KNOW 리노 GLOBAL ★

20,086 Aufrufe • vor 7 Monaten

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

starmex

357,179 Aufrufe • vor 1 Monat

I HAVEN’T OPENED A SINGLE BOOK THIS MONTH. CLAUDE READ 34 OF THEM FOR ME I built a vault in Obsidian, connected Claude and added Notebooklm went to sleep woke up with flashcards, mind maps, and an AI that answers from my own notes only my friends are still highlighting pdfs manually the only thing separating us is one setup: claude + obsidian + notebooklm every idea captured. every book processed. zero knowledge lost if this is the setup you’ve been looking for - like & bookmark so you don’t lose it
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I HAVEN’T OPENED A SINGLE BOOK THIS MONTH. CLAUDE READ 34 OF THEM FOR ME I built a vault in Obsidian, connected Claude and added Notebooklm went to sleep woke up with flashcards, mind maps, and an AI that answers from my own notes only my friends are still highlighting pdfs manually the only thing separating us is one setup: claude + obsidian + notebooklm every idea captured. every book processed. zero knowledge lost if this is the setup you’ve been looking for - like & bookmark so you don’t lose it

leopardracer

247,317 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 2 Monaten

THIS GUY SAW A $430 AI BILL AND BUILT HIS OWN AI LAB UNDER HIS DESK INSTEAD RTX 5090 + RTX 4090, 56GB VRAM, 128GB RAM, Proxmox and local Qwen / DeepSeek / Llama models running without API keys while everyone else is still paying every time they test a prompt. The best part of the setup: api_key: “not-needed”. His agents can scan GitHub, Reddit and RSS feeds, read notes, test ideas overnight and break without turning into another invoice. If something fails, he fixes the config, not the credit card limit. Most people rent AI by the token. He is turning a desk setup into a private machine that works even when the dashboard is closed.
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THIS GUY SAW A $430 AI BILL AND BUILT HIS OWN AI LAB UNDER HIS DESK INSTEAD RTX 5090 + RTX 4090, 56GB VRAM, 128GB RAM, Proxmox and local Qwen / DeepSeek / Llama models running without API keys while everyone else is still paying every time they test a prompt. The best part of the setup: api_key: “not-needed”. His agents can scan GitHub, Reddit and RSS feeds, read notes, test ideas overnight and break without turning into another invoice. If something fails, he fixes the config, not the credit card limit. Most people rent AI by the token. He is turning a desk setup into a private machine that works even when the dashboard is closed.

Gipp 🦅

69,445 Aufrufe • vor 1 Monat

A 16-YEAR-OLD DEVELOPER BUILT AN AI EMPLOYEE THAT WORKS 24 HOURS A DAY FOR LESS THAN $20 He stopped treating AI like a chatbot and turned it into a complete production system powered by Claude, Cursor and automated workflows Every morning the pipeline generated new ideas, wrote scripts, organized research and prepared content before he even opened his laptop What used to take an entire afternoon now takes less than 30 minutes, cutting production costs while multiplying output every single week The biggest lesson wasn't that AI works faster It was that the people building repeatable systems are moving ahead of creators still doing everything manually The biggest advantage in 2026 won't be talent It will be automation Bookmark this
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A 16-YEAR-OLD DEVELOPER BUILT AN AI EMPLOYEE THAT WORKS 24 HOURS A DAY FOR LESS THAN $20 He stopped treating AI like a chatbot and turned it into a complete production system powered by Claude, Cursor and automated workflows Every morning the pipeline generated new ideas, wrote scripts, organized research and prepared content before he even opened his laptop What used to take an entire afternoon now takes less than 30 minutes, cutting production costs while multiplying output every single week The biggest lesson wasn't that AI works faster It was that the people building repeatable systems are moving ahead of creators still doing everything manually The biggest advantage in 2026 won't be talent It will be automation Bookmark this

RetroChainer

13,378 Aufrufe • vor 15 Tagen

Imran Khan Pushed into Military Vehicle in Viral Video Pak Public Silence Draws Criticism In the video former Prime Minister of Pakistan and one of the most popular figures in the country Imran Khan can be seen being pushed with great disrespect and humiliation by soldiers of Pakistan’s military regime into a military vehicle. Imran Khan rendered tireless services for Pakistan and its people striving to elevate the country’s name on the global stage. He made every effort to free the people of Pakistan from the influence of the U.S. and what he described as an oppressive military establishment. Imran Khan sacrificed a life of comfort and privilege something only a few people in the world ever attain for the sake of the people of Pakistan. But now it appears that the people of Pakistan have betrayed him and they are not even able to come out raise their voices or ensure that he is taken to a hospital for treatment. It is a matter of great shame that when you needed him he sacrificed everything for you, but when he needs you, you only look for 100 excuses even to take him to a hospital. Shame.
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Imran Khan Pushed into Military Vehicle in Viral Video Pak Public Silence Draws Criticism In the video former Prime Minister of Pakistan and one of the most popular figures in the country Imran Khan can be seen being pushed with great disrespect and humiliation by soldiers of Pakistan’s military regime into a military vehicle. Imran Khan rendered tireless services for Pakistan and its people striving to elevate the country’s name on the global stage. He made every effort to free the people of Pakistan from the influence of the U.S. and what he described as an oppressive military establishment. Imran Khan sacrificed a life of comfort and privilege something only a few people in the world ever attain for the sake of the people of Pakistan. But now it appears that the people of Pakistan have betrayed him and they are not even able to come out raise their voices or ensure that he is taken to a hospital for treatment. It is a matter of great shame that when you needed him he sacrificed everything for you, but when he needs you, you only look for 100 excuses even to take him to a hospital. Shame.

برهان الدین ‏| Burhan uddin

143,280 Aufrufe • vor 2 Monaten

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?
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BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?

Mr. Buzzoni

78,973 Aufrufe • vor 10 Tagen