Reading is not decoding information. It is meeting a mind. The same circuitry used to infer what a friend is thinking lights up when you read a paragraph. AI text activates that circuitry perfectly, then leaves it with no one to find. You turned up for a conversation and the other chair is empty.

Six mechanisms land as one event. There is no intention behind the word choices, so inferences close on air. The relevance bargain breaks: too many sentences, too little return. Surprise is gone, because the model sits at the statistical centre of everything ever written. The sender spent a minute; the reader spends far longer. Smoothness used to mean skill. Now it often means automation. And the templates (lists of three, hedges, restated closings) get processed as pattern rather than message.

Scientific invention requires more than pattern recognition or formal proof. Following Einstein’s own account of discovery, it depends on an intuitive jump from experience to new axioms. Only after that jump does deduction and verification become possible.

Large language models have become strong at induction (extracting patterns from data) and are rapidly improving at deduction (reasoning from given premises). What they still lack is the capacity for the abductive jump itself: the generation of novel explanatory principles when existing ones are insufficient.

Anthropic researchers have identified a distinct internal workspace inside Claude — referred to as "J-space" — where thoughts appear to form before any tokens or words are generated. Suppressing this space allows basic recall but severely impairs complex, multi-step reasoning, suggesting it plays a fundamental role in cognition.

John Nosta connects this discovery to global workspace theory from cognitive neuroscience, which proposes a shared, flexible mechanism for chaining reasoning, integrating information, and making results available across different parts of a system. The emergence of a similar structure in a non-biological model raises a profound question: Are there universal first principles of thought that arise whenever sufficient complexity and training dynamics are present?