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The Debate over Understanding in AI's Large Language Models[pdf] (arxiv.org)
2 points by kelseyfrog on Mar 24, 2023 | hide | past | pdf | discuss on HN

In plain words: A review lays out the arguments for and against saying large language models truly understand language and the situations it describes. It concludes that a new science of intelligence could map different kinds of understanding and how to combine them.

Abstract · The Debate Over Understanding in AI's Large Language Models

We survey a current, heated debate in the AI research community on whether large pre-trained language models can be said to "understand" language -- and the physical and social situations language encodes -- in any important 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 a new 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.

Melanie Mitchell, David C. Krakauer
arXiv:2210.13966 · cs.LG, cs.AI · submitted Oct 14, 2022 · updated Feb 10, 2023
abstract · pdf · html · Under submission as a Perspective article. Updated with additional discussion and citations

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