Open generative AI models areaway forward for science

被引：23
|
作者：
Spirling, Arthur [1 ]
机构：
[1] NYU, Polit & Data Sci, New York, NY 10012 USA
来源：
NATURE | 2023年 / 616卷 / 7957期
关键词：
Ethics; Machine learning; Technology; Scientific community;
D O I：
10.1038/d41586-023-01295-4
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Researchers should avoid the lure of proprietary models and develop transparent large language models to ensure reproducibility.
引用
收藏
页码：413 / 413
页数：1
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