Does AI research need "world models" more than bigger LLMs?
It seems that generating hypotheses is no longer the main problem.
The harder problem may be continuously collecting real-world data, building accurate world models, and using them to guide experiments.
Is this where automated research is heading?
By “world model,” I mean a model continuously updated from experimental or sensor data, not just an LLM trained on text.