Language models feed from the same source. They carry as much claim to intelligence, it's the same intelligence. What makes language models inferior today is the lack of access to feedback signals. They are not embodied, embedded and enacted in the environment (the 4 E's). They don't even have a code execution engine to iterate on bugs. But they could have.

And when a models does have access to massive experimentation, search and can learn from its outcomes, like AlphaGo, then it can beat us at our own game. Trained just in self-play mode, learning from verifying outcomes, was enough to surpass two thousand years of history, all of our players put together.

I think future code generation models will surpass human level based on massive problem solving experience, and most of it will be generated by its previous version. A human could not experience as much in a lifetime.

This is the second source of intelligence - experience. For language models it only costs money to generate, it's not a matter of getting more human data. So the path is wide open now. Who has the money to crank out millions of questions, problems and tasks + their solutions?