Lummox
@Lummox_eth • 4,863 subscribers
like connecting & building & AI
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THE NEXT AI WORKER MAY COST $500 AND SIT BEHIND YOUR MONITOR. Mini PCs are becoming the cheapest path to private AI. A Mac Mini M4 starts at $599, Geekom AX8 Pro starts near $529, and MinisForum pushes up to 128GB RAM for local AI workloads. Ollama turns that hardware into a personal model server. No cloud fee. No data storage bill. No waiting for another SaaS product to decide your limits. Market shift is simple -> computer is moving back to the desk. Owning a mini PC is starting to look less like buying hardware and more like hiring a quiet AI operator.
Lummox387,398 次观看 • 2 天前
a 23-year-old guy built an AI animation factory in one weekend. $12,345 last month. 4 hours of direction total. > Claude writes scripts and scene breakdowns: 10 minutes. > Midjourney generates every frame: 20 minutes. > Runway animates every scene: 15 minutes. > ElevenLabs voices every character: 10 minutes. > Suno scores every episode: 5 minutes. > Make publishes to YouTube, Patreon, and X: 0 minutes. total: $124/month 4 content types running in parallel. 8 uploads per week. he sleeps. it produces. every prompt is in the article above.
Lummox79,170 次观看 • 20 天前
HERMES AGENT CROSSED 140,000 GITHUB STARS IN 3 MONTHS AND JUST BECAME THE MOST USED AGENT IN THE WORLD. Most AI agents forget everything between sessions. Hermes writes its own skills from experience. Next time it runs the skill, improves it, and gets faster. Independent benchmarks show agents with 20+ self-created skills complete similar tasks 40% faster than fresh instances. Qwen 3.6 where the 35B version outperforms last year's 120B models at one third the memory footprint. DGX Spark with 128GB unified memory running everything locally at $0 per month after hardware. The setup takes 30 minutes. LM Studio plus Qwen 3.6 27B for the model server. One install script for Hermes. One config connecting them. Set context window to 65,536 tokens or nothing works. After one month of daily use your skills directory has 20 to 50 learned workflows. Your Hermes is genuinely different from anyone else's.
Lummox69,484 次观看 • 24 天前
THE CHINESE INSTALLED 6 AI AGENTS RUNNING 24/7 FOR $11 A MONTH. THE BOX UNDER ONE DESK REPLACED $1,200 IN CLOUD SUBSCRIPTIONS. The Minisforum MS-S1 Max ships with 128GB of unified memory shared between CPU and GPU. Qwen3-Coder 30B runs at 40 to 50 tokens per second. 6 agents run simultaneously without anyone watching the meter. An inbox sorter drafts replies every 15 minutes. A research monitor watches 30+ feeds and lands a digest by 7 AM, a job that costs $15 to $20 a day on cloud APIs. The same stack on cloud subscriptions ran $800 to $1,200 a month. The hardware costs $3,000 once. Break-even hits month 3 to 4. The real shift is behavior, not savings. A meeting prep agent never would have justified per-token cost. Running it free overnight made it obvious.
Lummox14,093 次观看 • 8 天前
JIM SIMONS NEVER HAD A LOSING YEAR IN 34 ATTEMPTS. HERE IS THE 5 LAYER PIPELINE BEHIND IT. Spring 1988. A Cold War mathematician fired every trader and replaced them with signal detectors. $60 billion in performance fees. 39% annual returns after a 44% fee. Zero losing years. Layer 1 : Hurst exponent. Below 0.45 fades work. Above 0.55 momentum works. Medallion switches strategy automatically based on regime. Layer 2 : Factor decomposition. Renaissance runs 200+ factors privately. High alpha plus low R-squared means your edge is unexplained by known factors. Layer 3 : Markov Chain regime modeling. 76% Bear probability over 5 periods means no long positions. The model decides before you do. Layer 4 : Neural net. Three outputs : long, short, flat. Not predicting price. Predicting direction probability. 52% accuracy Kelly-sized correctly still prints money. Layer 5 : Execution. Half-Kelly sizing. Hard 2% risk cap. Edge must exceed execution cost by 1.5x minimum. This is where 80% of quants bleed out. 400 people. One shared model. The edge was never a single formula. It was always the pipeline.
Lummox24,056 次观看 • 18 天前
21 videos per week. 150,000 views daily. $3,000-$10,000 a month YouTube's algorithm does not reward the most creative creators. It rewards the ones who publish 4 times a week without breaking down. One video takes a full day. Description alone is 45 minutes. Multiply that by 4 uploads per week and the math breaks you. Most channels pay not because the content is weak but because the creator runs out of bandwidth. Claude solves the production bottleneck directly. Feed it your raw idea and speaking points. A tech channel publishing twice per week earns around $300 monthly at 50,000 views. The same creator using Claude to publish before a single sponsorship lands. The content does not get worse. YouTube interprets that as authority and pushes the channel harder.
Lummox19,502 次观看 • 25 天前
One iPhone with iOS 18.2. A Gumroad account. $18,200 in 12 months. Apple Intelligence wrote 80% of the first drafts. The formula is simple : > AI creates the raw material > you package and price it > the internet distributes. 5 revenue streams built on free platforms. Prompt packs on Gumroad generated $6,840. A weekly newsletter on Substack brought $4,320. One ebook on Amazon KDP added $3,060. Medium articles paid $2,190. Notion templates closed the gap at $1,830. The fastest product to ship is a prompt pack. 30 to 50 tested prompts for a specific use case, $9 to $15 on Gumroad, 3 hours to build. One guide published in month 4 made $340 in 90 days from 2 hours of work.
Lummox13,989 次观看 • 27 天前
NVIDIA is creating two completely different futures In one they put AI infrastructure on your property In the other they put it on your own desk ///// OPTION 1 A box worth more than most houses gets installed outside You provide the location, power and connectivity In return, you get perks like cheaper electricity, backup power and upgraded internet while AI workloads run around the clock You're not buying the hardware You're hosting it ///// OPTION 2 You spend a few thousand dollars on a DGX Spark Small enough to sit beside your monitor Powerful enough to run serious AI models locally No cloud bill No rented GPUs No sending sensitive data somewhere else The interesting part isn't the hardware It's the shift that's happening For years, AI belonged to giant tech companies and massive data centers Now NVIDIA is pushing a world where regular people can either host the infrastructure or own a piece of it themselves
Lummox10,019 次观看 • 27 天前
Another Chinese student made $400K for last 30 days He used Markov Chains and Claude Even without little knowledge you can make money on it How it works : > Markov Property : future depends only on the current state > State Space : the set of all possible states in the system > Transition Probability : the chance of moving from one state to another > Transition Matrix : a table of all transition probabilities between states > Steady State : the long-run equilibrium distribution as steps → infinity Just using these 5 rules you will be able to trade with 55%-65% wr Chinese trader has 71% wr and $418k PNL Account : Top formulas for trading so : 1) The Markov Property RSI = 100 - (100 / (1 + RS)) RS = Avg Gain / Avg Loss (N=14) RSI > 70 → Sell | RSI < 30 → Buy 2) State Distribution SMA = (P1+P2+...+PN) / N EMA = P×k + EMA_prev×(1-k), k = 2/(N+1) Fast MA crosses UP → Buy (Golden Cross) Fast MA crosses DOWN → Sell (Death Cross) 3) Expected Value EV = (p × W) − (q × L) p = win prob q = 1 − p W = profit if win L = loss if lose My result is 66,3% and $780 profit for last week I keep on learning trading every day and going to make my first $10k Trade with me :
Lummox11,242 次观看 • 2 个月前
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