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NO1ennn

@N01ennn • 3,043 subscribers

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

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

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A 21-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE. THE PART THAT MATTERS ISN'T THE SPEED, IT'S THAT NONE OF THEM CAN LIE TO HIM he opens the dashboard and shows the swarm live, 300 Kimi K2.6 agents firing in parallel, then Opus 4.8 checking every single output against its source. this is not just a faster swarm. it is a loop that refuses to stop while anything is still wrong he pointed it at 100 EV-market companies. first pass: 12 failed. wrong revenue, dead citations, empty fields. second pass: 3 failed. third pass: zero this is not another agent demo. it is a system that catches its own mistakes before he reads a single row
0:30
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A 21-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE. THE PART THAT MATTERS ISN'T THE SPEED, IT'S THAT NONE OF THEM CAN LIE TO HIM he opens the dashboard and shows the swarm live, 300 Kimi K2.6 agents firing in parallel, then Opus 4.8 checking every single output against its source. this is not just a faster swarm. it is a loop that refuses to stop while anything is still wrong he pointed it at 100 EV-market companies. first pass: 12 failed. wrong revenue, dead citations, empty fields. second pass: 3 failed. third pass: zero this is not another agent demo. it is a system that catches its own mistakes before he reads a single row

NO1ennn

6,939,174 views • 25 days ago

FOUR DIFFERENT VENDORS ARE NOW SHIPPING GB10 MINI PCs WITH 128GB UNIFIED MEMORY, AND ONE MICROTIK CRS 804 SWITCH CAN CONNECT UP TO EIGHT OF THEM INTO A 1 TERABYTE LOCAL AI CLUSTER 00:00 he points at the MikroTik CRS 804, "you need some kind of switch that'll handle QSFP56 ports like these", the interconnect that makes the whole cluster possible the GB10 ecosystem is no longer just Nvidia. Dell Pro Max GB10, ASUS Ascent GX10, and MSI Edge Expert all ship the same Grace Blackwell Superchip with 128GB of coherent memory. same silicon, different cases, same 200 gigabit ports on the back the CRS 804 is what connects them at prosumer prices. four 400 gigabit QSFP56 ports on one 1U chassis, breakout cables that split each port into two 200 gigabit lanes. one switch drives eight GB10 units in parallel do the math. eight nodes at 128GB each equals 1024GB of pooled unified memory across the cluster. run vLLM, shard a frontier model across all eight, and inference happens locally on hardware that fits in half a rack the real limiter revealed in the stress test was never throttling. it was interconnect topology, exactly the layer this switch fixes at a fraction of enterprise switch pricing $400 a month for combined chatgpt pro and claude code max hits $4,800 a year per developer. a small team of five running through this cluster pays back inside eight months and never expires the article covers the buying ladder for a single desk. this post is proof of the cluster ladder that starts where the desk one ends save this before the GB10 lineup grows past four vendors and prosumer cluster switches move upmarket
1:05
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FOUR DIFFERENT VENDORS ARE NOW SHIPPING GB10 MINI PCs WITH 128GB UNIFIED MEMORY, AND ONE MICROTIK CRS 804 SWITCH CAN CONNECT UP TO EIGHT OF THEM INTO A 1 TERABYTE LOCAL AI CLUSTER 00:00 he points at the MikroTik CRS 804, "you need some kind of switch that'll handle QSFP56 ports like these", the interconnect that makes the whole cluster possible the GB10 ecosystem is no longer just Nvidia. Dell Pro Max GB10, ASUS Ascent GX10, and MSI Edge Expert all ship the same Grace Blackwell Superchip with 128GB of coherent memory. same silicon, different cases, same 200 gigabit ports on the back the CRS 804 is what connects them at prosumer prices. four 400 gigabit QSFP56 ports on one 1U chassis, breakout cables that split each port into two 200 gigabit lanes. one switch drives eight GB10 units in parallel do the math. eight nodes at 128GB each equals 1024GB of pooled unified memory across the cluster. run vLLM, shard a frontier model across all eight, and inference happens locally on hardware that fits in half a rack the real limiter revealed in the stress test was never throttling. it was interconnect topology, exactly the layer this switch fixes at a fraction of enterprise switch pricing $400 a month for combined chatgpt pro and claude code max hits $4,800 a year per developer. a small team of five running through this cluster pays back inside eight months and never expires the article covers the buying ladder for a single desk. this post is proof of the cluster ladder that starts where the desk one ends save this before the GB10 lineup grows past four vendors and prosumer cluster switches move upmarket

NO1ennn

59,085 views • 8 days ago

INTEL JUST SHIPPED A WORKSTATION CARD WITH TWO GPUs ON ONE PCB AND 48GB OF VRAM. FOUR CARDS GIVE A SINGLE MOTHERBOARD 192GB OF POOLED INFERENCE MEMORY FOR THE PRICE OF TWO RTX 5090s 00:14 he holds one card up to the camera, two GPU dies side by side under the cooler, each one running its own x8 PCIe lane back to the chipset the cluster sees eight discrete accelerators in software. intel's Battle Matrix stack shards a model across all eight, so a 235B parameter network loads in slices and answers requests in parallel what 192GB of VRAM unlocks: an entire 200B class model in memory without quantization. a vision agent reading 100 invoices at once. a research box that holds three frontier models loaded simultaneously, switching between them in under a second intel is the slow side of inference. nvidia is faster per token, that is the honest tradeoff. but the only other path to this much VRAM is a $40,000 nvidia rack or three networked Mac Studios four B60 cards plus the chassis lands under $5,000. power draw averages 800 watts, $55 a month in electricity. one engineer paying $400 a month for combined ChatGPT Pro and Claude Code Max pays the hardware off in less than a year
1:16
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INTEL JUST SHIPPED A WORKSTATION CARD WITH TWO GPUs ON ONE PCB AND 48GB OF VRAM. FOUR CARDS GIVE A SINGLE MOTHERBOARD 192GB OF POOLED INFERENCE MEMORY FOR THE PRICE OF TWO RTX 5090s 00:14 he holds one card up to the camera, two GPU dies side by side under the cooler, each one running its own x8 PCIe lane back to the chipset the cluster sees eight discrete accelerators in software. intel's Battle Matrix stack shards a model across all eight, so a 235B parameter network loads in slices and answers requests in parallel what 192GB of VRAM unlocks: an entire 200B class model in memory without quantization. a vision agent reading 100 invoices at once. a research box that holds three frontier models loaded simultaneously, switching between them in under a second intel is the slow side of inference. nvidia is faster per token, that is the honest tradeoff. but the only other path to this much VRAM is a $40,000 nvidia rack or three networked Mac Studios four B60 cards plus the chassis lands under $5,000. power draw averages 800 watts, $55 a month in electricity. one engineer paying $400 a month for combined ChatGPT Pro and Claude Code Max pays the hardware off in less than a year

NO1ennn

48,054 views • 15 days ago

HERMES AGENT NOW RUNS ON AN 8GB LAPTOP GPU JUST AS EASILY AS IT RUNS ON A 128GB MINI PC Nous Research shipped the official Hermes Agent Desktop App this week. Someone pointed it at a local llama server running on an RTX 4060 with 16GB system RAM. The integration took two minutes The model behind it: Gemma 4 26B MoE, QAT quantized, running on 8GB of VRAM. A 60k token prompt held a stable 20 tokens a second, flat, no slowdown as context grew. The flags were nothing exotic, just -cmoe -c 248000 on llama.cpp What that 8GB setup does out of the box: reads and patches its own code, runs it in a terminal, debugs errors, manages GitHub repos, spawns sub-agents for parallel work. Browses the web with vision to debug a UI. Schedules cron jobs in plain language. Connects to Notion, Google Workspace, Linear, and Obsidian to manage tasks on its own That's the same agent layer running on a Minisforum MS-S1 MAX with 128GB of unified memory, 96GB of it to the GPU, holding a 120B model at 56 tokens a second instead of a 26B model at 20. Same software, same tool execution, same zero API key. The only thing that changes between an $800 laptop and a $2,000 mini PC is how big a model you can afford to run underneath it The barrier to running a real autonomous agent locally didn't just drop. It dropped all the way down to hardware most people already own
0:20
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HERMES AGENT NOW RUNS ON AN 8GB LAPTOP GPU JUST AS EASILY AS IT RUNS ON A 128GB MINI PC Nous Research shipped the official Hermes Agent Desktop App this week. Someone pointed it at a local llama server running on an RTX 4060 with 16GB system RAM. The integration took two minutes The model behind it: Gemma 4 26B MoE, QAT quantized, running on 8GB of VRAM. A 60k token prompt held a stable 20 tokens a second, flat, no slowdown as context grew. The flags were nothing exotic, just -cmoe -c 248000 on llama.cpp What that 8GB setup does out of the box: reads and patches its own code, runs it in a terminal, debugs errors, manages GitHub repos, spawns sub-agents for parallel work. Browses the web with vision to debug a UI. Schedules cron jobs in plain language. Connects to Notion, Google Workspace, Linear, and Obsidian to manage tasks on its own That's the same agent layer running on a Minisforum MS-S1 MAX with 128GB of unified memory, 96GB of it to the GPU, holding a 120B model at 56 tokens a second instead of a 26B model at 20. Same software, same tool execution, same zero API key. The only thing that changes between an $800 laptop and a $2,000 mini PC is how big a model you can afford to run underneath it The barrier to running a real autonomous agent locally didn't just drop. It dropped all the way down to hardware most people already own

NO1ennn

40,079 views • 23 days ago

AI kids videos. 60 seconds to make. $4,000 per 100K views. she figured it out first Pixar Flow + ChatGPT. pick template. write prompt. video ready. upload. repeat kids channels already pulling millions of views. all AI. nobody noticed yet YouTube RPM kids content: $200-$4,000 per 100K views. one viral video = month of salary month 12 at one video/week: $8,000-$15,000/month. $66/month stack. zero humans involved
0:32
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AI kids videos. 60 seconds to make. $4,000 per 100K views. she figured it out first Pixar Flow + ChatGPT. pick template. write prompt. video ready. upload. repeat kids channels already pulling millions of views. all AI. nobody noticed yet YouTube RPM kids content: $200-$4,000 per 100K views. one viral video = month of salary month 12 at one video/week: $8,000-$15,000/month. $66/month stack. zero humans involved

NO1ennn

71,060 views • 1 month ago

THE MS-A2 IS THE MINISFORUM BOX HERMES AGENT WAS NEVER MEANT TO RUN ON, AND THAT'S BY DESIGN The MS-S1 MAX earns its spot running Hermes Agent because of one thing. 128GB of unified memory, up to 96GB of it handed straight to the GPU. That's the only reason a 120B model fits and runs locally for $0 a month The MS-A2 solves a different problem. Ryzen 9 9955HX, 16 cores, 32 threads, up to 96GB of regular DDR5-5600, no unified pool Three M.2 PCIe 4.0 slots, one U.2, two 22110. Dual 10Gbps SFP+ LAN plus 2.5G. WiFi 6E. Bluetooth 5.3. A slide-out motherboard for fast upgrades. A real PCIe x16 slot that actually takes a low-profile GPU That last part is where the two machines split for good. The MS-S1 MAX's PCIe slot won't take a GPU at all, every bit of GPU power has to come from the unified chip itself. The MS-A2 trades that unified memory trick for raw expandability instead One box runs a local AI agent. The other runs a home lab that needs storage, networking, and room to grow. Minisforum built both on purpose, not as the same product wearing two names
1:06
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THE MS-A2 IS THE MINISFORUM BOX HERMES AGENT WAS NEVER MEANT TO RUN ON, AND THAT'S BY DESIGN The MS-S1 MAX earns its spot running Hermes Agent because of one thing. 128GB of unified memory, up to 96GB of it handed straight to the GPU. That's the only reason a 120B model fits and runs locally for $0 a month The MS-A2 solves a different problem. Ryzen 9 9955HX, 16 cores, 32 threads, up to 96GB of regular DDR5-5600, no unified pool Three M.2 PCIe 4.0 slots, one U.2, two 22110. Dual 10Gbps SFP+ LAN plus 2.5G. WiFi 6E. Bluetooth 5.3. A slide-out motherboard for fast upgrades. A real PCIe x16 slot that actually takes a low-profile GPU That last part is where the two machines split for good. The MS-S1 MAX's PCIe slot won't take a GPU at all, every bit of GPU power has to come from the unified chip itself. The MS-A2 trades that unified memory trick for raw expandability instead One box runs a local AI agent. The other runs a home lab that needs storage, networking, and room to grow. Minisforum built both on purpose, not as the same product wearing two names

NO1ennn

25,119 views • 24 days ago

a 19 year old girl just coded a quant trading bot from a research paper. Codex did 90% of the work drop PDF into Codex. ask it to act like a quant researcher. get working strategy code strategy: perps DEX funding carry. market-neutral. collect the spread between longs and shorts live test results: > 4 closed positions > 96% of profit came from funding. not price direction > annualized: ~19% APR > price PnL: flat. that’s the point turning a research paper into something tradable used to mean hours. now it’s one PDF drop
0:46
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a 19 year old girl just coded a quant trading bot from a research paper. Codex did 90% of the work drop PDF into Codex. ask it to act like a quant researcher. get working strategy code strategy: perps DEX funding carry. market-neutral. collect the spread between longs and shorts live test results: > 4 closed positions > 96% of profit came from funding. not price direction > annualized: ~19% APR > price PnL: flat. that’s the point turning a research paper into something tradable used to mean hours. now it’s one PDF drop

NO1ennn

46,468 views • 1 month ago

a 21 year old makes $30,000/month. Pinterest photo. AI video. Shopify store. zero inventory Pinterest → ChatGPT → Higgsfield → TikTok → Shopify. one pipeline. $153,680 in sales > Pinterest: source model aesthetic > ChatGPT: converts image to video prompt > Higgsfield MCP: UGC-style video. iPhone aesthetic. 9:16 > TikTok Studio: millions of views. free traffic > Shopify: closes the sale 56 cents per video. agency charges $1,500 for the same format. 7 clients = $10,500/month. 85% margins 50 videos for $50. humans were the bottleneck
0:29
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a 21 year old makes $30,000/month. Pinterest photo. AI video. Shopify store. zero inventory Pinterest → ChatGPT → Higgsfield → TikTok → Shopify. one pipeline. $153,680 in sales > Pinterest: source model aesthetic > ChatGPT: converts image to video prompt > Higgsfield MCP: UGC-style video. iPhone aesthetic. 9:16 > TikTok Studio: millions of views. free traffic > Shopify: closes the sale 56 cents per video. agency charges $1,500 for the same format. 7 clients = $10,500/month. 85% margins 50 videos for $50. humans were the bottleneck

NO1ennn

35,382 views • 1 month ago

THIS AGENT LEARNS FROM EVERY TASK. BUILDS ITS OWN SKILLS. REMEMBERS EVERYTHING 100K GitHub stars in 53 days. 160K+ now. 26K forks. 1,000+ contributors. what makes it different: > completes a task > writes a reusable skill from experience > gets faster next use > three-tier memory: remembers your projects, preferences, environment across every session > 200+ models via OpenRouter. Claude, GPT, Grok, Gemini, Ollama local one command > Telegram, Discord, WhatsApp, iMessage one gateway > built-in cron scheduler. sub-agents. MCP servers. web search. code execution > runs on a $5 VPS. 24/7. from your phone most AI agents: blank slate every session. Hermes: remembers everything. always
0:56
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THIS AGENT LEARNS FROM EVERY TASK. BUILDS ITS OWN SKILLS. REMEMBERS EVERYTHING 100K GitHub stars in 53 days. 160K+ now. 26K forks. 1,000+ contributors. what makes it different: > completes a task > writes a reusable skill from experience > gets faster next use > three-tier memory: remembers your projects, preferences, environment across every session > 200+ models via OpenRouter. Claude, GPT, Grok, Gemini, Ollama local one command > Telegram, Discord, WhatsApp, iMessage one gateway > built-in cron scheduler. sub-agents. MCP servers. web search. code execution > runs on a $5 VPS. 24/7. from your phone most AI agents: blank slate every session. Hermes: remembers everything. always

NO1ennn

24,902 views • 1 month ago

$127K/year. $20/month. zero employees Claude connected to Shopify via MCP in 15 minutes. reads products, orders, customers live. edits in real time > Amazon. Etsy. Gumroad. Shopify > one agent. five platforms. same workflow team replaced: > content manager. designer. SEO. developer $8,000/month in salaries. replaced by $20/month
2:25
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$127K/year. $20/month. zero employees Claude connected to Shopify via MCP in 15 minutes. reads products, orders, customers live. edits in real time > Amazon. Etsy. Gumroad. Shopify > one agent. five platforms. same workflow team replaced: > content manager. designer. SEO. developer $8,000/month in salaries. replaced by $20/month

NO1ennn

22,516 views • 2 months ago

$2,272/month. $1.80 cost. $22 sale price. 1,122% margin bankrupt companies. public domain tech. Claude analyzes 50 patents at once. Alibaba manufactures. Amazon sells plant insert: $1.80 →1,122% margin > zero inventory risk > zero R&D > just Claude and a USPTO filter zero manual research. Claude automates the entire scan
1:05
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$2,272/month. $1.80 cost. $22 sale price. 1,122% margin bankrupt companies. public domain tech. Claude analyzes 50 patents at once. Alibaba manufactures. Amazon sells plant insert: $1.80 →1,122% margin > zero inventory risk > zero R&D > just Claude and a USPTO filter zero manual research. Claude automates the entire scan

NO1ennn

19,575 views • 2 months ago

21-YEAR-OLD DESIGNER WHO CAN’T CODE BUILT A FULL-STACK MOBILE APP IN 2 HOURS WHILE CURSOR WROTE EVERY LINE one prompt. Plan mode. Composer. React Native + backend + AI logic. 2 hours. zero code written by hand running tracker. Strava sync. AI coach that says “congratulations, you’re still slow.” the engineer on his team: $1,840 Anthropic bill. 11 prod incidents. 71% accept rate him: $47 bill. 0 incidents. 8% accept rate Tab acceptance rate is not productivity. it’s code you don’t understand with your name on git blame
1:00
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21-YEAR-OLD DESIGNER WHO CAN’T CODE BUILT A FULL-STACK MOBILE APP IN 2 HOURS WHILE CURSOR WROTE EVERY LINE one prompt. Plan mode. Composer. React Native + backend + AI logic. 2 hours. zero code written by hand running tracker. Strava sync. AI coach that says “congratulations, you’re still slow.” the engineer on his team: $1,840 Anthropic bill. 11 prod incidents. 71% accept rate him: $47 bill. 0 incidents. 8% accept rate Tab acceptance rate is not productivity. it’s code you don’t understand with your name on git blame

NO1ennn

15,287 views • 1 month ago

AD AGENCIES CHARGE $15,000/MONTH. CLAUDE JUST REPLACED THEM IN 30 SECONDS install one skill. type /ads. full ad strategy. competitor analysis. meta campaigns. creatives. graphs. done freelancer on a $3,000 ad project: > research: 6 hours. writing: 8 hours. margin: $1,750 > Claude API: $2-5. 45 minutes QA. margin: $2,990+ what /ads gives you: competitor analysis > scraped automatically competitor analysis > scraped automatically creative assets > generated inside Claude full strategy guide with graphs and numbers the bottleneck was never the model. it was the hours. those hours are gone
0:38
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AD AGENCIES CHARGE $15,000/MONTH. CLAUDE JUST REPLACED THEM IN 30 SECONDS install one skill. type /ads. full ad strategy. competitor analysis. meta campaigns. creatives. graphs. done freelancer on a $3,000 ad project: > research: 6 hours. writing: 8 hours. margin: $1,750 > Claude API: $2-5. 45 minutes QA. margin: $2,990+ what /ads gives you: competitor analysis > scraped automatically competitor analysis > scraped automatically creative assets > generated inside Claude full strategy guide with graphs and numbers the bottleneck was never the model. it was the hours. those hours are gone

NO1ennn

13,794 views • 1 month ago

38 million views. kids YouTube. AI generated. under 60 seconds to make type a prompt. click agent. click start. fully generated video ready to upload $200-$3,000 per 100K views. finance RPM goes higher. kids content already pulling millions. all AI. nobody stopped them month 12 at one video/week: $8,000-$15,000/month. $66/month stack. zero humans involved it’s gonna be so easy it’s gonna piss you off
0:42
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38 million views. kids YouTube. AI generated. under 60 seconds to make type a prompt. click agent. click start. fully generated video ready to upload $200-$3,000 per 100K views. finance RPM goes higher. kids content already pulling millions. all AI. nobody stopped them month 12 at one video/week: $8,000-$15,000/month. $66/month stack. zero humans involved it’s gonna be so easy it’s gonna piss you off

NO1ennn

12,093 views • 1 month ago

20 year old. no model. no budget. $15,000/month. AI influencer + Shopify Pinterest → Claude → Higgsfield → Shopify. one photo. one pipeline. zero real model 5 Claude methods inside: > competitor autopsy - finds the angle nobody is using > bad review mining - free market research before first sale > email sequence - 22% of revenue. zero ad spend. runs itself > UGC ad script - looks filmed by accident > Sunday diagnostic - paste analytics. Claude finds what’s broken month 1: $1,200 → month 3: $8,400. net: $3,485
0:29
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20 year old. no model. no budget. $15,000/month. AI influencer + Shopify Pinterest → Claude → Higgsfield → Shopify. one photo. one pipeline. zero real model 5 Claude methods inside: > competitor autopsy - finds the angle nobody is using > bad review mining - free market research before first sale > email sequence - 22% of revenue. zero ad spend. runs itself > UGC ad script - looks filmed by accident > Sunday diagnostic - paste analytics. Claude finds what’s broken month 1: $1,200 → month 3: $8,400. net: $3,485

NO1ennn

12,524 views • 1 month ago

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