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index.html
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<!doctype html>
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<html>
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</html>
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<html>
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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" />
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
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max-width: 720px;
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margin: 0 auto;
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padding: 2rem 1.5rem;
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color: #1a1a2e;
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line-height: 1.6;
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background: #fff;
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}
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.center { text-align: center; }
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h1 {
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font-size: 2rem;
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margin-bottom: 0.2rem;
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font-weight: 700;
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}
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h3 {
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font-size: 1.1rem;
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font-weight: 400;
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color: #333;
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margin-top: 0.2rem;
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margin-bottom: 0.3rem;
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}
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.sub {
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font-size: 0.75rem;
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letter-spacing: 0.15em;
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color: #888;
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margin-bottom: 1.5rem;
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}
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hr {
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border: none;
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border-top: 1px solid #e0e0e0;
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margin: 1.5rem 0;
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}
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h2 {
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font-size: 1.2rem;
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margin-top: 1.8rem;
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margin-bottom: 0.8rem;
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}
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ul {
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padding-left: 1.2rem;
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}
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li {
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margin-bottom: 0.4rem;
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}
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table {
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width: 100%;
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border-collapse: collapse;
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margin: 1rem 0;
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font-size: 0.95rem;
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}
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th, td {
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text-align: left;
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padding: 0.5rem 0.8rem;
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border-bottom: 1px solid #eee;
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}
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th {
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font-weight: 600;
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border-bottom: 2px solid #ddd;
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}
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a {
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color: #2563eb;
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text-decoration: none;
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}
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a:hover {
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text-decoration: underline;
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}
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.links a {
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margin-right: 1.5rem;
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}
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strong { font-weight: 600; }
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</style>
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</head>
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<body>
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<div class="center">
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<h1>Tinman Lab</h1>
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<h3>Autonomous Machines. Second-Order Systems.</h3>
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<div class="sub">AGENT MEMORY · ADVERSARIAL SAFETY · AGENTIC ECONOMY · PERCEPTION SYSTEMS · APPLIED RESEARCH</div>
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</div>
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<hr />
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<h2>Disposition Distillation</h2>
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<p>Tinman Lab develops <strong>Disposition Distillation (DD)</strong> — a multi-teacher distillation methodology that trains <em>how a model behaves</em> into weights, not system prompts. DD models plan before acting, acknowledge uncertainty, verify their own reasoning, and know what they don't know.</p>
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<ul>
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<li><strong>4-stage all-MIT pipeline</strong> — Kimi K2.5 → GLM-5 → MiniMax M2.7 → GLM-5</li>
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<li><strong>7 behavioral dispositions</strong> — Eager, Deliberate, Adversarial, Curious, Self-Improving, Humble, Persistent</li>
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<li><strong>On-device focus</strong> — 0.6B to 2B parameters, quantized for mobile and edge deployment</li>
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<li><strong>100% open training data</strong> — MIT-licensed teachers only, zero proprietary model outputs</li>
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</ul>
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<h2>Models</h2>
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<table>
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<thead>
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<tr><th>Model</th><th>Size</th><th>Description</th></tr>
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</thead>
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<tbody>
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<tr>
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<td><a href="https://huggingface.co/Tinman-Lab/tinman-code-0.6B">tinman-code-0.6B</a></td>
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<td>418 MB</td>
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<td>Coding assistant with meta-cognitive awareness — plans, verifies, flags uncertainty</td>
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</tr>
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</tbody>
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</table>
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<h2>Links</h2>
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<p class="links">
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<a href="https://tinmanlab.com">Website</a>
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<a href="https://github.com/tinmanlabsl/">GitHub</a>
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<span style="color: #888;">Research Paper — coming soon</span>
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</p>
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</body>
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</html>
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