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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.18027397 |
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Table of Contents:
- <p>This release provides the first stable and citable version of the research project "AI Investment, Compute, and Institutional Shifts: A Reproducible Meta-Dataset and Integrated Analysis".</p> <h3>Contents</h3> <ul> <li>Full research paper (<code>paper.md</code>, <code>paper.pdf</code>)</li> <li>Reproducible data-processing pipeline (<code>build_meta_dataset.py</code>)</li> <li>Derived datasets (aggregations A–C)</li> <li>Figures corresponding to RQ1–RQ3</li> <li>Documentation and licensing information</li> </ul> <h3>Research scope</h3> <p>The release integrates four open-data secondary datasets and addresses three fixed research questions:</p> <ol> <li>Long-run institutional shifts in AI system building (Institutional Shift Index, 1950–2023)</li> <li>Co-evolution of private AI investment and training compute (indexed time series)</li> <li>Association between training compute and benchmark performance (MMLU)</li> </ol> <h3>Reproducibility</h3> <p>All results are generated from read-only raw inputs via a single script. See <code>README.md</code> for exact reproduction instructions.</p> <h3>Citation</h3> <p>A DOI is assigned via Zenodo upon release and should be used for citation.</p>