Colourless green ideas sleep furiously

Let's start by defining some terms.

Information Space: the total result of the semantic and lexical activity of humanity, "the world of names and titles" conjugated to the ontological world.

A large language model (LLM) consists of a neural network with many parameters (typically billions of weights or more), trained on large quantities of unlabelled text using self-supervised learning. LLMs emerged around 2018 and perform well at a wide variety of tasks. This has shifted the focus of natural language processing research away from the previous paradigm of training specialized supervised models for specific tasks.

Chat GPT 4 is a language model developed by OpenAI that uses deep learning techniques to generate human-like text. It is based on the transformer architecture, which is a neural network that can process sequential data,  and it is pre-trained on a vast corpus of text data.

An empirical observation, of mine essentially, is that the information space mapped by the n-dimensional vectors generated is far more sparsely populated than one might imagine. This has profound epistemological implications.

Prodnose: Eh?

Myself: Ah'm jess sayin' is all. Don' mean nothin' by it.

Prodnose: No more coffee or sugar for you until tomorrow at the earliest.