| Compute trends across three eras of machine learning J Sevilla, L Heim, A Ho, T Besiroglu, M Hobbhahn, P Villalobos 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 308 | 2022 |
| Will we run out of data? An analysis of the limits of scaling datasets in machine learning P Villalobos, J Sevilla, L Heim, T Besiroglu, M Hobbhahn, A Ho arXiv preprint arXiv:2211.04325, 2022 | 170* | 2022 |
| Red-Teaming the Stable Diffusion Safety Filter J Rando, D Paleka, D Lindner, L Heim, F Tramčr ML Safety Workshop NeurIPS 2022, 2022 | 113 | 2022 |
| Machine learning model sizes and the parameter gap P Villalobos, J Sevilla, T Besiroglu, L Heim, A Ho, M Hobbhahn arXiv preprint arXiv:2207.02852, 2022 | 59 | 2022 |
| Towards best practices in AGI safety and governance: A survey of expert opinion J Schuett, N Dreksler, M Anderljung, D McCaffary, L Heim, E Bluemke, ... arXiv preprint arXiv:2305.07153, 2023 | 48 | 2023 |
| Measuring what Really Matters: Optimizing Neural Networks for TinyML L Heim, A Biri, Z Qu, L Thiele arXiv preprint arXiv:2104.10645, 2021 | 42 | 2021 |
| International Governance of Civilian AI: A Jurisdictional Certification Approach R Trager, B Harack, A Reuel, A Carnegie, L Heim, L Ho, S Kreps, R Lall, ... Oxford Martin AI Governance Initiative Report, 2023 | 24 | 2023 |
| Estimating Training Compute of Deep Learning Models J Sevilla, L Heim, A Ho, M Hobbhahn, T Besiroglu, P Villalobos https://epochai.org/blog/estimating-training-compute, 2022 | 16 | 2022 |
| Parameter, Compute and Data Trends in Machine Learning J Sevilla, P Villalobos, JF Cerón, M Burtell, L Heim, AB Nanjajjar, A Ho, ... https://epochai.org/data/mlinputs, 2021 | 16 | 2021 |
| Computing Power and the Governance of Artificial Intelligence G Sastry, L Heim, H Belfield, M Anderljung, M Brundage, J Hazell, ... arXiv preprint arXiv:2402.08797, 2024 | 14 | 2024 |
| Visibility into AI Agents A Chan, C Ezell, M Kaufmann, K Wei, L Hammond, H Bradley, E Bluemke, ... The 2024 ACM Conference on Fairness, Accountability, and Transparency, 958-973, 2024 | 12 | 2024 |
| The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny? T Besiroglu, SA Bergerson, A Michael, L Heim, X Luo, N Thompson arXiv preprint arXiv:2401.02452, 2024 | 10 | 2024 |
| Trends in Machine Learning Hardware M Hobbhahn, L Heim, G Aydos https://epochai.org/blog/trends-in-machine-learning-hardware, 2023 | 10 | 2023 |
| Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers J Egan, L Heim arXiv preprint arXiv:2310.13625, 2023 | 9* | 2023 |
| Responsible Reporting for Frontier AI Development N Kolt, M Anderljung, J Barnhart, A Brass, K Esvelt, GK Hadfield, L Heim, ... arXiv preprint arXiv:2404.02675, 2024 | 7 | 2024 |
| Chinese firms are evading chip controls T Fist, L Heim, J Schneider Foreign Policy, 2023 | 7* | 2023 |
| Estimating PaLM’s training cost L Heim https://blog.heim.xyz/palm-training-cost/, 2022 | 6 | 2022 |
| Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation L Heim, T Fist, J Egan, S Huang, S Zekany, R Trager, MA Osborne, ... arXiv preprint arXiv:2403.08501, 2024 | 5 | 2024 |
| Hardware-Enabled Governance Mechanisms: Developing Technical Solutions to Exempt Items Otherwise Classified Under Export Control Classification Numbers 3A090 and 4A090 G Kulp, P Puri, D Gonzales, MJD Vermeer, E Smith, L Heim, Z Winkelman RAND Corporation, 2024 | 5* | 2024 |
| Compute at Scale: A Broad Investigation into the Data Center Industry K Pilz, L Heim arXiv preprint arXiv:2311.02651, 2023 | 5 | 2023 |
Anson HoEpoch AIVerified email at epochai.org
