"Words Are a Byproduct of Consciousness — For LLMs, It's the Other Way Around"
Devarsh Ranpara has published a thoughtful essay exploring a deceptively simple question: Where do your words come from?
For humans, the answer seems intuitive. An idea forms first — a concept, a feeling, an image — and then we reach for language to wrap around it. The word is the skin; consciousness is the thing underneath. For a large language model, the process is exactly inverted. An LLM predicts the next token based solely on the sequence of tokens that came before it. There is no idea sitting beneath the surface. The words are the entire story; any appearance of meaning is a byproduct that emerges by accident.
Ranpara traces this asymmetry through the history of human communication technology: spoken language, writing, the printing press, the computer, the internet, and finally the Transformer architecture that gave us modern LLMs. At each inflection point, humans gained new ways to transmit ideas, but the direction of flow — from thought to expression — never changed. LLMs reverse that flow, and Ranpara argues that this direction cannot be meaningfully replicated.
The essay also touches on a practical concern: as LLM-generated content fills the open web, future models will be trained on increasingly synthetic data. "An LLM can give you perfect grammar and a rich vocabulary," Ranpara writes, "but it can quietly lose the real context."
Still, the tone is cautiously optimistic. Ranpara notes that early computers were also expensive and power-hungry, and within three quarters of a century they shrank into our pockets. "All of human knowledge is now sitting inside a small chat box. We just need a few smart humans who can imagine."
The piece concludes that in a world where anyone can execute, the differentiating factors become consistency and noise-cutting — not raw intelligence. Engineers, he suggests, remain safe because "coding was never the hard part anyway. That kind of thinking is the real thing."