--- title: TinyThink sdk: gradio short_description: Interactive visualization of recursive reasoning concepts authors: - raayraay - samiksha-bc sdk_version: 6.3.0 --- # 🧠 TinyThink: Glass-Box Reasoning Visualization An **interactive educational demo** that visualizes the concept of recursive reasoning from the paper ["Less is More: Recursive Reasoning with Tiny Networks"](https://github.com/SamsungSAILMontreal/TinyRecursiveModels) (Samsung SAIL Montreal, 2025). ## What This Demo Shows This Space provides a visual explanation of how **Tiny Recursive Models (TRM)** approach complex reasoning tasks: - **Step-by-step visualization** of how a model iteratively refines its answer - - **ARC-AGI style puzzles** rendered with the official 10-color palette - - **Educational content** explaining the recursive reasoning mechanism - ## ⚠️ Important Note - **This is a visualization/simulation demo, not actual TRM inference.** The animation demonstrates the *concept* of recursive refinement—showing how a model progressively improves its answer over multiple iterations. - For the real model implementation, see: - - 📄 [Paper & Code](https://github.com/SamsungSAILMontreal/TinyRecursiveModels) - - 🤗 [Model Checkpoints](https://huggingface.co/arcprize/trm_arc_prize_verification) - ## The Key Insight - The TRM achieves **45% on ARC-AGI-1** with only **7M parameters** by using: - 1. **Recursive depth over model size** – Multiple "thinking" iterations 2. 2. **Latent state refinement** – The model updates internal representations z 3. 3. **Progressive answer improvement** – Each iteration corrects previous errors 4. This challenges the "bigger is better" paradigm in AI reasoning. 4. ## Try It Out 3. Select different ARC-AGI puzzles and watch the visualization of how recursive reasoning progressively transforms an initial guess into the correct solution. - --- *Created as an educational tool to make AI research accessible. Inspired by the innovative work of Samsung SAIL Montreal.*