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     <p>
         An experimental Hybrid AI integrating a Large Language Model (Qwen 3) with biologically-inspired neuromorphic memory via the SELSC Engine. Capable of real-time neurogenesis and dopamine-modulated fast-weight learning.
     </p>
+
+    <div style="max-width: 800px; margin-bottom: 3rem; text-align: left; background: rgba(255,255,255,0.03); padding: 2rem; border-radius: 1rem; border: 1px solid rgba(255,255,255,0.1);">
+        <h2 style="color: #60a5fa; margin-top: 0;">Technical Overview</h2>
+        <ul style="color: #cbd5e1; line-height: 1.8;">
+            <li><strong>Core LLM:</strong> Qwen 3 (0.6B) - Optimized for high-speed reasoning.</li>
+            <li><strong>Memory Engine:</strong> SELSC v2 (Synaptic Evolved Learning State Controller).</li>
+            <li><strong>Learning Logic:</strong> Online Hebbian learning with custom dopamine-gated reward heads.</li>
+            <li><strong>Architecture:</strong> SNN-LLM Hybrid with dynamic synaptic growth (Neurogenesis).</li>
+        </ul>
+        <p style="font-size: 1rem; margin-top: 1rem;">This project explores the intersection of transformer architectures and spiking neural networks, aiming to solve catastrophic forgetting in localized training environments.</p>
+    </div>
+
     <div class="links-container">
         <!-- Backlink to Space Apps -->
         <a href="https://huggingface.co/spaces/Specialgfhdhdh/learning-qwen-space" target="_blank">
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             <span class="icon">📦</span> Download the Model
         </a>
     </div>
+
+    <footer style="margin-top: 4rem; color: #475569; font-size: 0.9rem;">
+        &copy; 2026 Specialgfhdhdh Research | Built with SELSC Engine v2
+    </footer>
 </body>
 </html>