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index.html
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<html>
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<!DOCTYPE html>
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<html lang="de">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>🚀 Skills Blog</title>
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<style>
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* { margin: 0; padding: 0; box-sizing: border-box; }
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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min-height: 100vh;
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padding: 20px;
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}
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.container {
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max-width: 800px;
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margin: 0 auto;
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}
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header {
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text-align: center;
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color: white;
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margin-bottom: 40px;
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}
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header h1 {
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font-size: 3rem;
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margin-bottom: 10px;
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}
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header p {
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font-size: 1.2rem;
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opacity: 0.9;
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}
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.post {
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background: white;
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border-radius: 12px;
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padding: 30px;
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margin-bottom: 20px;
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box-shadow: 0 10px 30px rgba(0,0,0,0.2);
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}
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.post h2 {
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color: #333;
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margin-bottom: 5px;
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font-size: 1.5rem;
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}
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.post .tag {
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display: inline-block;
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background: #667eea;
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color: white;
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padding: 3px 10px;
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border-radius: 20px;
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font-size: 0.75rem;
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margin-bottom: 10px;
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}
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.post .date {
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color: #888;
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font-size: 0.85rem;
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margin-bottom: 15px;
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}
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.post .content {
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color: #444;
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line-height: 1.7;
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white-space: pre-line;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<header>
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<h1>🚀 Skills</h1>
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<p>Blog über Fähigkeiten und Kompetenzen</p>
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</header>
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<div class="post">
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<span class="tag">AI Development</span>
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<h2>🐑 Ralph Wiggum - Iterative AI Loops</h2>
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<div class="date">29. Dezember 2025</div>
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<div class="content">Ralph Wiggum ist eine Entwicklungstechnik für iterative KI-Agentenschleifen. Benannt nach Ralph Wiggum aus den Simpsons.
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Das Konzept: Ein einfacher Bash-Loop, der wiederholt einen Prompt an einen KI-Agenten füttert.
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Core Commands:
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• /ralph-loop - Startet eine iterative Schleife
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• /cancel-ralph - Bricht die Schleife ab</div>
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</div>
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<div class="post">
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<span class="tag">Interpretability</span>
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<h2>🔍 Google Gemma Scope 2</h2>
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<div class="date">29. Dezember 2025</div>
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<div class="content">Google DeepMind hat Gemma Scope 2 veröffentlicht - eine umfassende Suite von Interpretability-Tools für Gemma 3.
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Key Features:
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• Full-Stack Interpretability
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• 270M bis 27B Parameter
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• 110 Petabytes an Daten
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• Veröffentlicht am 19. Dezember 2025</div>
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</div>
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<div class="post">
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<span class="tag">Mechanistic Interpretability</span>
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<h2>🎛️ Steering mit Neuronpedia & Gemma 3</h2>
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<div class="date">29. Dezember 2025</div>
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<div class="content">Neuronpedia ist eine Open-Source-Plattform für KI-Steering und Experimente.
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Mit Gemma Scope 2 bietet Neuronpedia:
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• Sparse Autoencoders (SAEs) und Transcoders
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• Interactive Steering capabilities
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• Systematische Neuronen-Analyse
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Transcoders übertreffen SAEs bei der Interpretability!</div>
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</div>
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</div>
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</body>
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</html>
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