将语言模型作为半导体机器：通过结构主义和后结构主义语言理论重概念构AI语言系统

本文提出了一种新框架，用以重新概念化大型语言模型（LLMs），将其视为半导体机器而非人类认知的模仿。drawing from structuralist and post-structuralist theories of language—specifically the works of Ferdinand de Saussure and Jacques Derrida—I argue that LLMs should be understood as models of language itself, aligning with Derrida's concept of 'writing' (l'ecriture)。 The paper is structured into three parts. First, I lay the theoretical groundwork by explaining how the word2vec embedding algorithm operates within Saussure's framework of language as a relational system of signs. Second, I apply Derrida's critique of Saussure to position 'writing' as the object modeled by LLMs, offering a view of the machine's 'mind' as a statistical approximation of sign behavior. Finally, the third section addresses how modern LLMs reflect post-structuralist notions of unfixed meaning, arguing that the 'next token generation' mechanism effectively captures the dynamic nature of meaning. By reconceptualizing LLMs as semiotic machines rather than cognitive models, this framework provides an alternative lens through which to assess the strengths and limitations of LLMs, offering new avenues for future research.