Binance Charts 💎💎💎

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Binance Charts 💎💎💎

Binance Charts 💎💎💎

@gemwhisperer

Trader who loves undervalued coins & TA addict with proper FA ability. Follow for calls & crypto threads. No advice & DYOR. #EnterBeforeFOMO

Singapore Katılım Nisan 2018
214 Takip Edilen1.5K Takipçiler
Binance Charts 💎💎💎 retweetledi
Joseph Tsar
Joseph Tsar@joseph_tsar_·
Full Course On How To Speak Brilliantly
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CyrilXBT
CyrilXBT@cyrilXBT·
You're going to watch Netflix tonight anyway. But if you give me 5 hours instead - I'll give you a skill that will still be rare in 2026. This N8N full course teaches you to BUILD and AUTOMATE anything: → No-code workflows → AI agent pipelines → Systems that run while you sleep The people who watch this tonight will have a real edge. The people who skip it will still be trading time for money next year, wondering why nothing moved. Video below. Are you actually going to watch it or just save this and forget it?
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Kirill
Kirill@kirillk_web3·
CLAUDE FULL COURSE 4 HOURS This is the most detailed Claude guide I’ve seen online. Bookmark this before you forget. 4 hours. Build tools. Automate work. Learn how people build bots and systems. Claude → Tools → Automation → Products → Money
Kirill@kirillk_web3

x.com/i/article/2031…

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CyrilXBT
CyrilXBT@cyrilXBT·
INSTEAD OF WATCHING NETFLIX TONIGHT. Spend 1 hour with this. Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything. The people who watch this tonight will wake up tomorrow with a skill that most people will not have in 2 years. The people who skip it will still be watching Netflix next year wondering why nothing in their life has changed. Your call.
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이사 dojjunn
이사 dojjunn@dojjunn·
STEP 1: Beli kapal 1,9T. tapi gk ada duit gimana dong? investor A,B,C dateng ngasih primary note "debt-to-asset acquisition" kapal kebeli, non-cash trx. kapalnya beli dari siapa? tentu saja dari investor yg ngasih primary note. STEP 2: gk lama kemudian mau right issue. tentu saja RInya buat bayar kapal tadi. investor lama gk ikut RInya, dialihin ke investor A,B,C. loh bukanya dia yg ngasih primary note? betul artinya koversinya dilakuin disini, A,B,C gk perlu keluar duit buat ikut RInya. bisa dibilang yg akan setor cash "hanya" ritel yg ikut RI. mas dojjunn, bukanya ini cuma muter2 asset doang? knp gk right issue aja langsung. YAA DISITULAH KENAPA INI ADA. saya yakin sedikit yg paham dan tentu aja gk ada yg peduli soal yg ribet2 beginian. masih gk paham juga? forget it, don't buy it.
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Arti Shah
Arti Shah@TechByArti·
Stop burning tokens on Claude Code. Use this instead 👇 A free GitHub repo (80K⭐) that turns your CLI into a high-performance AI coding system. Link → github.com/affaan-m/every… Why it’s different: → Token optimization Smart model selection + lean prompts = lower cost → Memory persistence Auto-save/load context across sessions (No more losing the thread) → Continuous learning Turns your past work into reusable skills → Verification loops Built-in evals to make sure code actually works → Subagent orchestration Handles large codebases with iterative retrieval Most people think Claude struggles with complex repos. It doesn’t. They’re just not using the right setup. This fixes that. Bookmark this for your AI stack. ♻️ #AI #Claude #AIAgents #LLM #GenAI #DevTools
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Julian Goldie SEO
Julian Goldie SEO@JulianGoldieSEO·
Claude AI FULL COURSE 5 HOURS (Build & Automate Anything)
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Google AI
Google AI@GoogleAI·
We’re launching a brand new, full-stack vibe coding experience in @GoogleAIStudio, made possible by integrations with the @Antigravity coding agent and @Firebase backends. This unlocks: — Full-stack multiplayer experiences: Create complex, multiplayer apps with fully-featured UIs and backends directly within AI Studio — Connection to real-world services: Build applications that connect to live data sources, databases, or payment processors and the Antigravity agent will securely store your API credentials for you — A smarter agent that works even when you don't: By maintaining a deeper understanding of your project structure and chat history, the agent can execute multi-step code edits from simpler prompts. It also remembers where you left off and completes your tasks while you’re away, so you can seamlessly resume your builds from anywhere — Configuration of database connections and authentication flows: Add Firebase integration to provision Cloud Firestore for databases and Firebase authentication for secure sign-in This demo displays what can be built in the new vibe coding experience in AI Studio. Geoseeker is a full-stack application that manages real-time multiplayer states, compass-based logic, and an external API integration with @GoogleMaps 🕹️
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Market Rebellion
Market Rebellion@RebellioMarket·
22 TECHNICAL ANALYSIS TOPICS YOU NEED TO LEARN: (Bookmark it) 1.Fibonacci Retracements 2.Breakouts 3.Elliott Waves 4.Reversal 5.Fair Value Gap 6.Candlesticks 7.Heikin Ashi 8.Moon Phases 9.Renko 10.Harmonic Patterns 11.Support &Resistance 12.Dynamic Support &Resistance 13.Trendlines 14.Gann Angles 15.Momentum Indicators 16.Oscillators 17.Divergences 18.Volume 19.Supply & Demand 20.Market Structure 21.Break of Structure (BOS)& 22.CHOCH
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GrumpierByTheDay
GrumpierByTheDay@GrumpierBTDay·
A very good book:
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AI Panda
AI Panda@AIPandaX·
this guy literally drops banger after banger:
AI Panda tweet mediaAI Panda tweet mediaAI Panda tweet mediaAI Panda tweet media
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SΛGΞWHΛLΞ.HL✦
SΛGΞWHΛLΞ.HL✦@SageWhale·
Hyperliquid just became the most profitable chain on the planet in the last 24 hours hyperliquid generated more fees than ethereum, solana, bitcoin and BNB chain combined With just 11 employees, no VCs or marketing
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Kshitij Mishra | AI & Tech
Kshitij Mishra | AI & Tech@DAIEvolutionHub·
Fastest growing GitHub projects this week 🤯 1. agency-agents (+23.2K) AI agency in one repo 2. superpowers (+19.2K) framework for AI agents 3. MiroFish (+17.6K) swarm intelligence engine 4. OpenViking (+10.2K) context DB for agents 5. browser (+9.9K) headless browser for AI 6. impeccable (+6.4K) design system for AI UI 7. page-agent (+6.2K) control websites with AI 8. context-hub (+5.2K) Andrew Ng’s agent layer 9. deepagents (+4.9K) multi-agent framework 10. BitNet (+4.8K) 1-bit LLMs by Microsoft AI agents took over GitHub 😭 x.com/DAIEvolutionHu…
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Noisy
Noisy@noisyb0y1·
me after reading a free article and understanding I could make more than the professor who charged me 5 years of my life to teach me nothing practical
Noisy@noisyb0y1

x.com/i/article/2033…

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Nav Toor
Nav Toor@heynavtoor·
🚨 Hedge fund managers are going to hate this. Someone just open sourced a system that does their entire job. 30.5% annualized returns. $0 in fees. It's called TradingAgents. Not one AI agent. An entire simulated trading firm. Analysts, researchers, traders, and risk managers. All AI. All arguing with each other before making a single trade. No Bloomberg Terminal. No $50K data feeds. No MBA required. Here's what's inside this thing: → 4 AI analysts scanning financials, news, social sentiment, and technicals → A Bull and Bear researcher that literally debate each other → A trader that synthesizes every argument into a final call → A risk management team that can veto any trade → A fund manager that approves or rejects execution Here's the wildest part: It beat every traditional trading strategy they benchmarked. Cumulative returns. Sharpe ratio. Max drawdown. All of them. Hedge funds charge 2% management + 20% performance fees for this exact workflow. This is free. 100% Open Source.
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Alex
Alex@de1lymoon·
MiroFish: 1,000,000 AI agents are debating your future How it works: - You upload a news item, report, or event - The system builds a graph of relationships between entities - It launches thousands of agents with different beliefs - The agents debate, influence each other’s opinions, and form coalitions - A map of possible scenarios emerges from the chaos The only formula that matters after that is: EV = p · W − (1 − p) · L Where p is the frequency of the scenario in the simulation 1,000,000 runs. It happened 3200 times. p ≈ 0.32
Alex@de1lymoon

Stop Guessing the Market. Start Running Simulations Most models try to predict the future. MiroFish does it differently: it simulates it p ≈ 320 / 1000 → EV = pW − (1 − p)L Instead of giving you one forecast, MiroFish builds a digital world from news, policy drafts, earnings reports, and market signals then fills it with thousands of AI agents and lets them react > They argue > They set up camps > They amplify narratives > They change their beliefs under pressure And after hundreds or thousands of runs, you don’t get a prophecy you get scenario frequencies. > If one outcome happens 320 times out of 1000, then p ≈ 0.32 From there, it becomes a decision problem: - calculate Expected Value - compare your probability to the market’s - use Kelly to size the bet correct

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