Update README.md

README.md

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----
-license: mit
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+---
+license: mit
+datasets:
+- interstellarninja/hermes_reasoning_tool_use
+- crownelius/Opus-4.6-Reasoning-2100x-formatted
+- ronantakizawa/github-top-code
+base_model:
+- nvidia/Cosmos-Reason2-2B
+---
+
+
+
+# Karla C1: The Adaptive Brain for Physical AI
+
+**Karla C1** is a novel, continuous-learning architecture designed for Physical AI and embodied agents. Built on top of **NVIDIA Cosmos-Reason2-2B**, it solves the problem of catastrophic forgetting in robotics by implementing a **Nested Learning Architecture** [1] with *Surprise-Based Plasticity*.
+
+## The Vision: Physical AI on the Edge
+
+Robots in the real world encounter new tools and constraints daily. Karla allows an agent to learn a new physical tool or API *on the fly* during inference, modifying its own weights in seconds on consumer hardware (e.g., RTX 4060 Ti), without ever forgetting its foundational knowledge.
+
+## Architecture: Nested Learning
+
+Instead of a standard transformer pipeline, Karla acts as a multi-frequency brain based on the Nested Learning (NL) paradigm [1]:
+
+1. **L0 (The Subconscious): NVIDIA Cosmos-Reason2-2B (Frozen).** Provides world-class reasoning, semantic understanding, and syntax. Loaded in 4-bit to save VRAM.
+2. **L1 (The RAM): Dynamic Knowledge MoE (64 Experts).** A fast, GPU-based Mixture of Experts. It updates *live during inference* using Delta Gradient Descent [1], memorizing new facts and tool syntaxes instantly.
+3. **L2 (The Frontal Lobe): Continuous Thought Machine (CTM).** Based on Sakana AI's research [2], this is a parallel sequence-level reasoning module. It takes Cosmos's hidden states + L1 knowledge and "thinks" for $T$ internal ticks before outputting an action plan.
+
+> [!WARNING]
+> The L2 module currently faces stability issues where the CTM's internal dynamics can lead to token repetition during long reasoning chains.
+
+## Quickstart
+
+```bash
+pip install torch transformers datasets pandas accelerate bitsandbytes
+cd Karla
+python chat.py
+
+```
+
+## TODO
+
+* [ ] Train Longer
+* [ ] Make L1 Inference Learning Intensity variable
+* [ ] Give the model control over itself
+* [ ] Fix stuttering
+
+## Datasets Used
+
+* `interstellarninja/hermes_reasoning_tool_use`
+* `crownelius/Opus-4.6-Reasoning-2100x-formatted`
+* `ronantakizawa/github-top-code`
+
+## References
+
+[1] Behrouz, A., Razaviyayn, M., Zhong, P., & Mirrokni, V. (2025). **Nested Learning: The Illusion of Deep Learning Architecture**. *Google Research*. [arXiv:2512.24695](https://arxiv.org/abs/2512.24695)
+
+[2] Darlow, L., Regan, C., Risi, S., Seely, J., & Jones, L. (2025). **Continuous Thought Machines**. *Sakana AI*. [arXiv:2505.05522](https://arxiv.org/abs/2505.05522)