The debate over understanding in AI's large language models.
The debate over understanding in AI's large language models.
复制标题
在人工智能的大型语言模型中关于理解的辩论。
DOI：
10.1073/pnas.2215907120
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发表时间：
2023-03-28
影响因子：
11.1
通讯作者：
Krakauer, David C.
中科院分区：
文献类型：
--
作者：
Mitchell, Melanie;Krakauer, David C.
我们在人工智能（AI）研究社区中调查了当前的激烈辩论，以说明我们在任何人类的意义上都可以说，可以说大型的语言模型以及物理和社交状况的语言编码。鉴于这些论点，我们认为，对更广泛的智力科学的理解和关键问题。开发的，将洞悉不同的理解方式，它们的优势和局限性以及整合潜水员认知形式的挑战。
We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition.
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D