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Dario Amodei
Dario Amodei
CEO and Co-Founder at Anthropic
Adresă de e-mail confirmată pe anthropic.com
Titlu
Citat de
Citat de
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Language models are few-shot learners
T Brown, B Mann, N Ryder, M Subbiah, JD Kaplan, P Dhariwal, ...
Advances in neural information processing systems 33, 1877-1901, 2020
398342020
Language models are unsupervised multitask learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
OpenAI blog 1 (8), 9, 2019
159332019
Deep speech 2: End-to-end speech recognition in english and mandarin
D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ...
International conference on machine learning, 173-182, 2016
39152016
Evaluating large language models trained on code
M Chen, J Tworek, H Jun, Q Yuan, HPDO Pinto, J Kaplan, H Edwards, ...
arXiv preprint arXiv:2107.03374, 2021
38272021
A cross-platform toolkit for mass spectrometry and proteomics
MC Chambers, B Maclean, R Burke, D Amodei, DL Ruderman, ...
Nature biotechnology 30 (10), 918-920, 2012
36542012
Deep reinforcement learning from human preferences
PF Christiano, J Leike, T Brown, M Martic, S Legg, D Amodei
Advances in neural information processing systems 30, 2017
34192017
Concrete problems in AI safety
D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané
arXiv preprint arXiv:1606.06565, 2016
31282016
Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2020
27332020
Learning to summarize with human feedback
N Stiennon, L Ouyang, J Wu, D Ziegler, R Lowe, C Voss, A Radford, ...
Advances in Neural Information Processing Systems 33, 3008-3021, 2020
18682020
Training a helpful and harmless assistant with reinforcement learning from human feedback
Y Bai, A Jones, K Ndousse, A Askell, A Chen, N DasSarma, D Drain, ...
arXiv preprint arXiv:2204.05862, 2022
16392022
Fine-tuning language models from human preferences
DM Ziegler, N Stiennon, J Wu, TB Brown, A Radford, D Amodei, ...
arXiv preprint arXiv:1909.08593, 2019
15342019
Constitutional ai: Harmlessness from ai feedback
Y Bai, S Kadavath, S Kundu, A Askell, J Kernion, A Jones, A Chen, ...
arXiv preprint arXiv:2212.08073, 2022
12732022
The malicious use of artificial intelligence: Forecasting, prevention, and mitigation
M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ...
arXiv preprint arXiv:1802.07228, 2018
12192018
AI and Compute
D Amodei, D Hernandez, G Sastry, J Clark, G Brockman, I Sutskever
4992018
Benchmarking safe exploration in deep reinforcement learning
A Ray, J Achiam, D Amodei
arXiv preprint arXiv:1910.01708 7 (1), 2, 2019
4772019
Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
D Ganguli, L Lovitt, J Kernion, A Askell, Y Bai, S Kadavath, B Mann, ...
arXiv preprint arXiv:2209.07858, 2022
4712022
Reward learning from human preferences and demonstrations in atari
B Ibarz, J Leike, T Pohlen, G Irving, S Legg, D Amodei
Advances in neural information processing systems 31, 2018
4572018
Characterizing deformability and surface friction of cancer cells
S Byun, S Son, D Amodei, N Cermak, J Shaw, JH Kang, VC Hecht, ...
Proceedings of the National Academy of Sciences 110 (19), 7580-7585, 2013
4212013
A general language assistant as a laboratory for alignment
A Askell, Y Bai, A Chen, D Drain, D Ganguli, T Henighan, A Jones, ...
arXiv preprint arXiv:2112.00861, 2021
3882021
Scaling laws for autoregressive generative modeling
T Henighan, J Kaplan, M Katz, M Chen, C Hesse, J Jackson, H Jun, ...
arXiv preprint arXiv:2010.14701, 2020
3812020
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