Pioneer of causal AI, Judea Pearl, argues that no amount of scaling will get LLMs to AGI.
— Big Brain AI (@realBigBrainAI) February 18, 2026
He believes current large language models face fundamental mathematical limitations that can't be solved by making them bigger.
"There are certain limitations, mathematical limitation that… pic.twitter.com/xEpBKQReEj
From the tweet:
When hospitals collect data on treatment effects, that raw data never reaches the LLMs.
Instead, the models consume doctors' written interpretations. Analyses shaped by people who already have a mental model of how disease and treatment work.
In other words, LLMs are learning from the map, not the territory.
