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Quite interesting post that asks the right question about "asking the right questions". Yet one aspect I felt missing (which might automatically solve this) is first-principles-based causal reasoning.
A truly intelligent system — one that reasons from first principles by running its own simulations and physical experiments — would notice if something doesn't align with the "textbook version".
It would recognize when reality deviates from expectations and ask follow-up questions, naturally leading to deeper insights and the right questions - and answers.
Fascinating in this space is the new "Reasoning-Prior" approach (MIT Lab & Harvard), which trains reasoning capabilities learned from the physical world as a foundation for new models (before evening learning about text).
Relevant paper: "General Reasoning Requires Learning to Reason from the Get-go."