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2025
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| Online Access: | https://doi.org/10.5281/zenodo.18027397 |
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| _version_ | 1866901661993140224 |
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| author | Cecilia, Jean |
| author_facet | Cecilia, Jean |
| 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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18027397 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI Investment, Compute, and Institutional Shifts (Reproducible Meta-Dataset) Cecilia, Jean <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> |
| title | AI Investment, Compute, and Institutional Shifts (Reproducible Meta-Dataset) |
| url | https://doi.org/10.5281/zenodo.18027397 |