Ridark (@ridark_eth)
@ridark_eth
Content Creator & Researcher | Web3 & BD/growth/smm
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APPLE IS LYING TO YOU ABOUT THE MAC MINI, AND THIS SUB-$100 FIX PERMANENTLY UNLOCKS ITS TRUE POWER
The Mac Mini is an absolute beast until you run out of ports in exactly 5 seconds and your system begins throttling to death under heavy video editing or gaming.
Most users waste hundreds on messy dongles and external hubs, completely destroying their desk aesthetics.
The ultimate power move is dropping a vertical, active-cooling dock right into your workstation ecosystem.
Why this layout changes everything:
The Thermal Shield: Integrated aluminum pads and a silent high-speed fan that completely eliminate system lag, heat build-up, and sudden freezing under load.
Extreme Expansion: Instantly unlocks triple-monitor support via multiple HDMI ports, high-speed USB arrays, and a hidden SSD slot.
Modular Integration: Bridges directly into the Mac's native ports using a flush, custom jump connector, keeping your desktop entirely cord-free.
Stop letting Apple gatekeep your machine's peak performance.
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THIS GUY SHOWED HOW HIS BROTHER MAKES $15,000 A MONTH MAKING ROBLOX GAMES WITH CLAUDE, WITHOUT WRITING A SINGLE LINE OF CODE HIMSELF
No dev team. No publisher. No computer science degree. Just a $20 Claude subscription and the Roblox Studio game engine.
He doesn't write code by hand or build game logic manually. Instead, Claude acts as his personal programmer.
Here is how the system works: he types what he wants in plain text: "create a script for a leaderboard" or "write a coin saving system" → Claude generates a ready-to-use piece of Lua code → he copies and pastes it directly into Roblox Studio → the game gets packed with mechanics.
And if something breaks, he just drops the error into the chat, and Claude provides detailed instructions, a list of fixes, and the corrected code. What would take a beginner weeks of studying documentation gets done in mere hours.
The money here doesn't come from subscriptions but from inside the game: players buy in-game items, passes, and cosmetics with Robux -> Roblox's currency. The creator then officially exchanges the accumulated Robux for real money through the Roblox Developer Exchange program.
He simply describes the kind of game he wants. Everything else -> from the very first line of Lua to a working game mechanic -> is handled by AI.
What do you think Claude Fable is capable of and how much money can he make you?
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I genuinely don't understand why everyone isn't using this yet
Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain.
You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets.
Here's the whole thing:
> Install Obsidian, create a vault, open it in Claude Code
> Paste Karpathy's wiki idea file and tell Claude to build it
> Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it
> Drop any source into raw and say "ingest this"
> Ask questions across everything, forever
Five minutes to set up, and you never start from a blank chat again.
Full step-by-step guide with Claude and Obsidian, link below.
Bookmark this
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19-year-old from china makes $9,000/month designing product sites and ships each one in an afternoon. here's his exact setup
the whole thing runs on two tools that each do one job:
> brief written by hand: 5 min
> Moonchild builds the design system, then every screen from it: 20 min
> MCP hands the design to Claude as real structure, not a screenshot: instant
> Claude Code reads those exact tokens and builds the live app: 20 min
> second Claude session reviews the build for drift: 10 min
total: about an hour. screen five still matches screen one. no agency, no dev, no design team
the trick is MCP. the design tool passes Claude the actual colors, components and layout, so it builds from the source instead of guessing from a picture.
full pipeline, every prompt, in the article above.
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NVIDIA doesn't want your backyard
It wants your electrical connection
That's the part most people are missing
Everyone sees headlines about homeowners getting paid to host AI infrastructure
What they don't realize is why companies are even considering this in the first place
Building a traditional data center can take years
AI demand is growing right now
So instead of waiting for new facilities, companies are exploring ways to push compute closer to existing power and internet connections
For homeowners, the pitch is pretty straightforward
Lower utility costs
Backup power
Hardware upgrades
Potential compensation for hosting equipment
Not life-changing money
But definitely enough to get attention
The real story isn't the monthly payment
It's that AI infrastructure is starting to leave industrial parks and move into residential areas
A few years ago that would've sounded ridiculous
Today it's being discussed as a serious solution to one of the biggest bottlenecks in the AI industry
The AI race isn't just about building better models anymore
It's about finding places to run them
And your neighborhood might end up being part of the answer
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A guy just built an entire tech company using nothing but parallel Claude Code agents.
Remember my post about building 6 trading bots in 15 minutes?
This is how you take that infrastructure and scale it into a self-managing AI factory.
The developer launched VibeHQ -> a system where multiple Claude instances mimic a real software development team.
He completely replaced traditional tech roles with autonomous AI agents:
> PM Agent specs the features
> Backend Agent deploys the database
> Frontend Agent builds the UI in real-time
> QA Agent stress-tests for bugs
No human developers. Just Claude instances talking to each other and deploying code.
If Claude Code can orchestrate an entire software agency on autopilot, imagine what it does to your trading infrastructure.
The era of doing any digital work manually is officially over.
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🚨 Claude Code made me 6 trading bots in 15 mins
In the US alone, emotional retail traders lost more than $1.8 billion on liquidations
While billions of amateur traders were staring at charts, overtrading, and getting wrecked on fees, a quiet group of algorithmic traders treated prediction markets like a hyper-liquid data engine
They didn't guess outcomes -> they knew the structural price gaps in advance
Here is how they did it, and why manual trading is completely dead:
It's all about removing emotion and deploying cross-market statistical arbitrage
Linear Spread Cointegration
Formula: S_t = P_P,t - β * P_K,t - μ
Ornstein-Uhlenbeck Continuous Dynamics
Formula: dS_t = θ(μ - S_t)dt + σ dW_t
Euler-Maruyama Discretization (MLE Calibration)
Formula: S_t_i = S_t_i-1 * e^(-θΔt) + μ(1 - e^(-θΔt)) + ε_t
Level 1 Order Book Imbalance (OBI)
Formula: I_t = (V_b(t) - V_a(t)) / (V_b(t) + V_a(t))
Volume-Weighted Micro-Price Prediction
Formula: P_micro(t) = P_mid(t) + I_t * (Δspread / 2)
Cross-Venue Predictive Signal Optimization
Formula: ΔP_Kalshi(t + δ) = f(I_Polymarket(t), P_micro,Polymarket(t) - P_micro,Kalshi(t))
In the era of advanced AI, the winner is not the one who guesses the score, but the one who lets automated systems execute with absolute patience and discipline.
AI does the hard parts now -> you don't even need a CS degree to build this
The full behind-the-scenes live system build is now available to the public 📝
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🚨 Claude Code made me 6 trading bots in 15 mins
In the US alone, emotional retail traders lost more than $1.8 billion on liquidations
While billions of amateur traders were staring at charts, overtrading, and getting wrecked on fees, a quiet group of algorithmic traders treated prediction markets like a hyper-liquid data engine
They didn't guess outcomes -> they knew the structural price gaps in advance
Here is how they did it, and why manual trading is completely dead:
It's all about removing emotion and deploying cross-market statistical arbitrage
Linear Spread Cointegration
Formula: S_t = P_P,t - β * P_K,t - μ
Ornstein-Uhlenbeck Continuous Dynamics
Formula: dS_t = θ(μ - S_t)dt + σ dW_t
Euler-Maruyama Discretization (MLE Calibration)
Formula: S_t_i = S_t_i-1 * e^(-θΔt) + μ(1 - e^(-θΔt)) + ε_t
Level 1 Order Book Imbalance (OBI)
Formula: I_t = (V_b(t) - V_a(t)) / (V_b(t) + V_a(t))
Volume-Weighted Micro-Price Prediction
Formula: P_micro(t) = P_mid(t) + I_t * (Δspread / 2)
Cross-Venue Predictive Signal Optimization
Formula: ΔP_Kalshi(t + δ) = f(I_Polymarket(t), P_micro,Polymarket(t) - P_micro,Kalshi(t))
In the era of advanced AI, the winner is not the one who guesses the score, but the one who lets automated systems execute with absolute patience and discipline.
AI does the hard parts now -> you don't even need a CS degree to build this
The full behind-the-scenes live system build is now available to the public 📝
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