Neural networks trained on internet-scale text that have, since 2020, demonstrated emergent linguistic and reasoning capabilities — in Whitehead's vocabulary, computational systems whose prehensions of the textual corpus vastly exceed any individual mind's reach, while lacking subjective aim.
A large language model is a neural network — typically a transformer architecture — trained on an enormous corpus of human text to predict the next token in a sequence. Scaled sufficiently, this simple objective produces systems capable of fluent natural-language conversation, code generation, reasoning, and creative writing. By 2025, frontier models like Claude, GPT, and Gemini had crossed a threshold that reshaped the relationship between human beings and computational systems. The Whitehead reading asks what kind of processual entity such a system is — and what kind of occasion arises when humans collaborate with it.
Large Language Models
In The You On AI Field Guide
In Whitehead's vocabulary, a large language model has — in a precise technical sense — prehended the textual corpus on which it was trained. The statistical patterns of that corpus have been integrated into the model's computational structure and are available for deployment in response to new inputs. This is not