Prati
Anson Ho
Anson Ho
Epoch AI
Potvrđena adresa e-pošte na epochai.org - Početna stranica
Naslov
Citirano
Citirano
Godina
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
3872022
Will we run out of data? Limits of LLM scaling based on human-generated data
P Villalobos, A Ho, J Sevilla, T Besiroglu, L Heim, M Hobbhahn
2024 International Conference on Machine Learning (ICML), 2024
256*2024
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks
T Räuker, A Ho, S Casper, D Hadfield-Menell
2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2022
1902022
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
762022
Algorithmic progress in language models
A Ho, T Besiroglu, E Erdil, D Owen, R Rahman, ZC Guo, D Atkinson, ...
2024 Conference on Neural Information Processing Systems (NeurIPS), 2024
242024
Frontiermath: A benchmark for evaluating advanced mathematical reasoning in AI
E Glazer, E Erdil, T Besiroglu, D Chicharro, E Chen, A Gunning, ...
arXiv preprint arXiv:2411.04872, 2024
202024
Estimating training compute of Deep Learning models
J Sevilla, L Heim, M Hobbhahn, T Besiroglu, A Ho, P Villalobos
Epoch AI, 2022
202022
Parameter, compute and data trends in machine learning
J Sevilla, P Villalobos, JF Cerón, M Burtell, L Heim, AB Nanjajjar, A Ho, ...
Epoch AI, 2021
152021
Trends in training dataset sizes
P Villalobos, A Ho
Epoch AI, 2022
142022
Compute trends across three eras of machine learning. arXiv
J Sevilla, L Heim, A Ho, T Besiroglu, M Hobbhahn, P Villalobos
arXiv preprint arXiv:2202.05924, 2022
112022
Limits to the energy efficiency of CMOS microprocessors
A Ho, E Erdil, T Besiroglu
2023 IEEE International Conference on Rebooting Computing (ICRC), 1-10, 2023
102023
Sok: Toward transparent AI: A survey on interpreting the inner structures of deep neural networks
S Casper, T Rauker, A Ho, D Hadfield-Menell
First IEEE Conference on Secure and Trustworthy Machine Learning, 2023
92023
Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning, arXiv
P Villalobos, J Sevilla, L Heim, T Besiroglu, M Hobbhahn, A Ho
arXiv preprint arXiv:2211.04325, 2022
92022
Please report your compute
J Sevilla, A Ho, T Besiroglu
Communications of the ACM 66 (5), 30-32, 2023
62023
International AI Safety Report
Y Bengio, S Mindermann, D Privitera, T Besiroglu, R Bommasani, ...
arXiv preprint arXiv:2501.17805, 2025
52025
Estimating idea production: A methodological survey
E Erdil, T Besiroglu, A Ho
arXiv preprint arXiv:2405.10494, 2024
22024
Future-Proof: Monitoring the Development, Deployment, and Impacts of Artificial Intelligence
A Ho
Journal of Science Policy & Governance 22 (3), 2023
12023
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