The Cybernetic Order-word: Tensors, Tensions and LLM Vector Spaces

Abstract

What happens when large language models (LLMs) begin to ‘speak’ like humans? Is it an instance of robot intelligence or reason? Or is it something else entirely? In this article I explore why what is really a matter of data analytics and statistical prediction is so readily assumed to be a display of real intelligence and even emergent cognition by genealogically tracing the relationship between machines, organisms and language. It becomes clear that machine–organism metaphors have a long history that can be traced back to René Descartes, which once again became prominent during the cognitive revolution and the subsequent development of cybernetics. Of interest is the role of Chomskyan linguistics in this history and critiques thereof by cognitive linguistics who argue for embodiment but retain some functionalist views, such as the primacy of mental representations. In recent work on enaction this is discarded and, as I show, enactive work on linguistic bodies brings us close to a Deleuzo-Guattarian understanding of language as assemblages of enunciation. Enactivists do not, however, have an explicit theory of technicity, which is where Bernard Stiegler, Gilles Deleuze and Félix Guattari provide correctives. Taken together, linguistic bodies, alongside Stiegler's theorisation of grammatisation and mnemotechnics, and Deleuze and Guattari's understanding of the translatability of language and of order-words as tensors provides us with an especially sophisticated framework for thinking about the Bayesian ordering of the world.