> I don't think any new languages will easily beat the existing ones, simply because of the mass of training data that is available.

Seems like a solvable problem though by generating synthetic data that’s guaranteed to be accurate through linters, compilers and tests.

If it’s ~9 figures to train a frontier model, it seems like training on a new language could be a rounding error if it was a priority.

I could see the appeal of a new agentic-friendly language that’s focused on minimizing tokens. The standard library could be massive with no concern of making the language easily readable or learnable.