The transformer architecture, introduced by Vaswani et al. (2017), is at the heart of the remarkable recent progress in the development of language models, including famous chatbots such as Chat-gpt and Bard. In this paper, I argue that we an extract from the way the transformer architecture works a picture of the relationship between context and meaning. I call this the transformer picture, and I argue that it is a novel with regard to two related philosophical debates: the contextualism debate regarding the extent of context-sensitivity across natural language, and the polysemy debate regarding how polysemy should be captured within an account of word meaning. Although much of the paper merely tries to position the transformer picture with respect to these two debates, I will also begin to make the case for the transformer picture.

翻译：Transformer架构（Vaswani等，2017）是近期语言模型（包括ChatGPT和Bard等著名聊天机器人）取得显著进展的核心。本文论证，我们可以从Transformer架构的运行方式中提取出语境与意义之间关系的图景，称之为"Transformer图景"。本文认为，这一图景相对于两项相关的哲学辩论而言具有新颖性：一是关于自然语言中语境敏感程度的语境主义辩论，二是关于如何在词义解释中处理多义性的多义性辩论。尽管本文主要致力于将该图景定位于上述两大辩论之中，但仍将开始论证该图景的合理性。