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Code and data to reproduce the analyses and figures for the Epoch AI Data Insight "Compute is not a bottleneck for robotic manipulation"

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Compute for Robotic Manipulation

Overview

This repository contains the code and data to reproduce the analyses and figures for the Epoch AI Data Insight: Compute is not a bottleneck for robotic manipulation.

The workflow is centered on a single Jupyter notebook, analysis.ipynb, which reads input data from data/.

Repository structure

  • analysis.ipynb: End-to-end analysis notebook that reproduces results and figures.
  • requirements.txt: Python dependencies to run the notebook.
  • data/
    • Robotics Models.csv: Core dataset of robotics models used in the analysis.
    • ML Models-full view.csv: Epoch's AI Models dataset, filtered to frontier AI models in the analysis.
    • robotics_models_docs.md: Definitions of key fields in Robotics Models.csv.

Quick start

  • Setup

    # from the repository root (this directory)
    python3 -m venv .venv
    source .venv/bin/activate    # Windows: .venv\Scripts\activate
    pip install -U pip
    pip install -r requirements.txt
  • Run the analysis interactively

    jupyter notebook   # or: jupyter lab

    Open analysis.ipynb and Run All cells. Outputs (tables/figures) will appear inline in the notebook. Some cells may optionally save files; if so, they save to the repository directory.

  • Run the analysis non-interactively (headless)

    jupyter nbconvert --to notebook --execute --inplace analysis.ipynb

    To generate a shareable HTML report:

    jupyter nbconvert --to html --execute --output analysis.html analysis.ipynb

Citation

If you use this code or data, please follow the instructions to cite the article at https://epoch.ai/data-insights/compute-for-robotic-manipulation.

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Code and data to reproduce the analyses and figures for the Epoch AI Data Insight "Compute is not a bottleneck for robotic manipulation"

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