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The paper investigates how ~10.6M-parameter Tiny Transformers can learn multi-step arithmetic using algorithmic scratchpads and a hierarchical developmental curriculum, showing division accuracy rising from 4.0% to 86.7% while identifying failure modes like catastrophic forgetting and poor generalization to unseen operand sizes.
A user discovered that Gemini dumped its internal scratchpad, including UI rendering logic, component names like Bento, and Knowledge Graph entity IDs, revealing previously undocumented details about its internal pipeline.
This tutorial explains how to extend a basic AI agent with long task planning capabilities by adding a scratchpad and to-do list tools, enabling the agent to manage complex tasks through step-by-step planning and tracking.