AutoResearch Framework
A reference guide for understanding how autonomous AI research works. This skill documents the methodology from karpathy/autoresearch for educational purposes.
What This Is
This skill does NOT run any code. It serves as a reference for understanding:
- Fixed time budget experiments (5 minutes)
- Metric-driven iteration (val_bpb)
- Single-file training scope
- Self-contained ML training setup
Key Concepts
| Concept | Description |
|---|---|
| val_bpb | Validation bits per byte — lower is better |
| Fixed Budget | Experiments run for exactly 5 minutes |
| Single Scope | One file to modify per experiment |
Architecture Overview
The framework consists of three files:
| File | Purpose |
|---|---|
| prepare.py | Data preparation (do not modify) |
| train.py | Model training loop reference |
| program.md | Research strategy template |
Design Patterns
- Fixed time budget: Makes experiments directly comparable
- Single file scope: Keeps changes manageable
- Metric-driven: Uses val_bpb to compare results
For Educational Use
This skill is a reference implementation based on karpathy/autoresearch by Andrej Karpathy. It demonstrates autonomous research methodologies used in modern AI development.
Inspiration
Based on karpathy/autoresearch by Andrej Karpathy.