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<div class="center">
<h1>Tinman Lab</h1>
<h3>Autonomous Machines. Second-Order Systems.</h3>
<div class="sub">AGENT MEMORY · ADVERSARIAL SAFETY · AGENTIC ECONOMY · PERCEPTION SYSTEMS · APPLIED RESEARCH</div>
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<hr />
<p>We build on-device AI systems that reason, remember, and self-correct β small models designed to run autonomously at the edge with calibrated uncertainty and adversarial robustness.</p>
<h2>Research Areas</h2>
<ul>
<li><strong>Agent Memory</strong> β Encrypted semantic memory infrastructure for persistent agent context</li>
<li><strong>Adversarial Safety</strong> β Multi-agent stress-testing and trust verification for autonomous systems</li>
<li><strong>Perception Systems</strong> β On-device vision, voice, and multimodal understanding</li>
<li><strong>Disposition Distillation</strong> β Training behavioral tendencies (planning, uncertainty acknowledgment, self-verification) into sub-billion parameter model weights via all-MIT multi-teacher distillation</li>
</ul>
<h2>Research Releases</h2>
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<tr><th>Model</th><th>Size</th><th>Description</th></tr>
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<td><a href="https://huggingface.co/Tinman-Lab/tinman-code-0.6B">tinman-code-0.6B</a></td>
<td>418 MB</td>
<td>Research release β Disposition Distillation proof-of-concept on Qwen3-0.6B</td>
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<h2>Links</h2>
<p class="links">
<a href="https://tinmanlab.com">Website</a>
<a href="https://github.com/tinmanlabsl/">GitHub</a>
<span style="color: #888;">Research Paper β coming soon</span>
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