Source · Tier B · PreprintSource · Computing Power and the Governance of Artificial Intelligence
Computing Power and the Governance of Artificial Intelligence
G. Sastry, L. Heim, H. Belfield, M. Anderljung, M. Brundage, J. Hazell, C. O'Keefe, G. K. Hadfield, R. Ngo, K. Pilz, G. Gor, E. Bluemke, S. Shoker, J. Egan, R. F. Trager, S. Avin, A. Weller, Y. Bengio, D. Coyle. 2024. arXiv.
| Original | https://arxiv.org/abs/2402.08797 |
|---|---|
| DOI | 10.48550/arXiv.2402.08797 |
| arXiv | 2402.08797 |
| Accessed | 2026-09-25 |
| Authored or published by | Oxford Martin AI Governance Initiative, Centre for the Governance of AI |
| Imported from | hodgkins-ai-verification-papers@c71e59ff0e8e |
| Note | Listed under "Motivations and policy proposals" in the Hodgkins bibliography (CC BY 4.0). Also listed on the Oxford Martin AI Governance Initiative's publications page (https://aigi.ox.ac.uk/publications/computing-power-and-the-governance-of-artificial-intelligence/, read 2026-09-24). Also presented as a GovAI research paper (https://www.governance.ai/research-paper/computing-power-and-the-governance-of-artificial-intelligence, read 2026-09-24). |
Cited by
- R1Chip registries and manufacturing records
- Communication between compute groups is bounded
- Compute stock is at most a declared amount
- This compute runs inference, not training
- There is no undeclared relevant compute
- A training run stayed within declared limits
- Compartmentalization
- FLOP accounting
- Inference and training workloads
- Interconnect bandwidth
- Undeclared compute
- Centre for the Governance of AI