The AI revolution is running out of data. What can researchers do?

IF 48.5 1区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Nature Pub Date : 2024-12-11 DOI:10.1038/d41586-024-03990-2

Nicola Jones

引用次数: 0

Abstract

AI developers are rapidly picking the Internet clean to train large language models such as those behind ChatGPT. Here’s how they are trying to get around the problem. AI developers are rapidly picking the Internet clean to train large language models such as those behind ChatGPT. Here’s how they are trying to get around the problem.

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人工智能革命正在耗尽数据。研究人员能做些什么？

人工智能开发人员正在迅速挑选互联网，以训练大型语言模型，如ChatGPT背后的语言模型。下面是他们试图解决这个问题的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature 综合性期刊-综合性期刊

CiteScore

90.00

自引率

1.20%

发文量

3652

审稿时长

3 months

期刊介绍： Nature is a prestigious international journal that publishes peer-reviewed research in various scientific and technological fields. The selection of articles is based on criteria such as originality, importance, interdisciplinary relevance, timeliness, accessibility, elegance, and surprising conclusions. In addition to showcasing significant scientific advances, Nature delivers rapid, authoritative, insightful news, and interpretation of current and upcoming trends impacting science, scientists, and the broader public. The journal serves a dual purpose: firstly, to promptly share noteworthy scientific advances and foster discussions among scientists, and secondly, to ensure the swift dissemination of scientific results globally, emphasizing their significance for knowledge, culture, and daily life.