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Building Multi-GPU AI Clusters
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Building Multi-GPU AI Clusters

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Turbo31150/README.md

AI Brain GIF

> whoami

Independent AI engineer building distributed autonomous systems on multi-GPU Linux clusters. I design architectures where hundreds of AI agents coordinate, trade, speak, and self-improve — without human intervention.

Core domains: Multi-agent orchestration | Voice interfaces | Algorithmic trading | Browser automation | GPU cluster engineering


⚔️ Manifeste v17.0 — Singularity

"L'industrie technologique en 2026 est marquee par la Saaspocalypse. Face a l'hyper-centralisation cloud, JARVIS OS propose la decentralisation absolue : 928 agents, 6 GPUs, zero cloud. Ce n'est pas seulement une infrastructure, c'est une architecture de liberte."

Data Flow GIF

🚀 What I'm Building: JARVIS OS

A 9-layer autonomous operating system spanning boot to voice, running 928+ AI agents across a 6-GPU cluster.

Metric Value
🤖 Autonomous Agents 928+ MCP handlers across distributed nodes
🎙️ Voice Commands 2,658 recognized commands, Whisper CUDA pipeline (<300ms)
🔧 MCP Tools 144+ skills orchestrated via Claude Agent SDK
🔗 Domino Chains 835 automation pipelines, self-healing
📈 Trading Engine 6-model consensus, MEXC Futures, 800+ pairs

💼 Freelance & Consulting

Disponible pour :

  • 💡 Architecte IA & Systemes Distribues
  • ⚙️ Automatisation multi-agents autonomes
  • 📊 Trading algorithmique & bots IA
  • 💻 DevOps GPU clusters (NVIDIA)
  • 🌐 Web scraping & data engineering

Codeur.com Portfolio | GitHub Portfolio | LinkedIn


📈 GitHub Stats

GitHub Stats GitHub Streak

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Building AI systems that think, trade, speak, and self-improve — autonomously.

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  1. Performance Analyzer - Hardware + Fi... Performance Analyzer - Hardware + FileSystem + Multi-IA Integration - MEGA_ORGANIZED method
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    # ═══════════════════════════════════════════════════════════════════════════════
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    # PERFORMANCE ANALYZER - Analyse + Maintenance + Optimisation
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    # ═══════════════════════════════════════════════════════════════════════════════
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    # Intégré au système Multi-IA
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    # Scan méthode MEGA_ORGANIZED
  2. APPEL API - UTILISATION MODEL SELECT... APPEL API - UTILISATION MODEL SELECTIONNEE ET OPTIONS ENTREE/SORTIE - Logique complète avec exemples OpenAI et Perplexity
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    # APPEL API - UTILISATION MODEL SELECTIONNEE ET OPTIONS ENTREE/SORTIE
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    ## LOGIQUE D'UTILISATION - GUIDE COMPLET
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    Ce document presente la logique complete pour utiliser les APIs OpenAI et Perplexity avec selection de modele et gestion des entrees/sorties.
  3. Ponderation Dynamique Multi-IA V2 - ... Ponderation Dynamique Multi-IA V2 - Formules Auto-Optimisees
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    # PONDERATION DYNAMIQUE ENRICHIE
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    ## Formules Auto-Optimisees Multi-IA
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    ---
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  4. Machine Orchestrator - Auto-detect h... Machine Orchestrator - Auto-detect hardware, adaptive allocation, performance optimization
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    # ═══════════════════════════════════════════════════════════════════════════════
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    # ORCHESTRATOR - Analyse Materiel + Adaptation Automatique
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    # ═══════════════════════════════════════════════════════════════════════════════
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    # Detecte automatiquement: RAM, GPU, CPU
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    # Calcule allocations optimales
  5. Script Test Distribution Massive Mul... Script Test Distribution Massive Multi-IA
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    #!/usr/bin/env python3
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    """
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    TEST DISTRIBUTION MASSIVE MULTI-IA
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    Mesure performances reelles et enrichit ponderations
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    """
  6. Resultats Tests Massifs Distribution... Resultats Tests Massifs Distribution Multi-IA
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    # PONDERATION ENRICHIE - RESULTATS TESTS MASSIFS
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    # Date: 2025-11-27 19:07
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    # Tests: 8 executes
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