The top comment on this thread was about AI models being easily distilled being a stroke of luck.

This should not be surprising at all. Every new students spends tiny fractions of time learning knowledge that took many lifetimes to discover. This fundamental to the progress of intelligence and understanding.

It should not be surprising that AI can be distilled. It's the logical method of training; I would hope that each frontier model is in fact not trained 'from scratch' each time.

We should expect future frontier models are simply distilled versions trained by specialist models, the same way humans learn from a series of professors, papers and canonical books on each different subject material. Models like this can be trained incrementally, or a so called Mixture of Experts (MoE).

Why not reply to that top comment? Its still there.

> This should not be surprising at all. Every new students spends tiny fractions of time learning knowledge that took many lifetimes to discover.

This argument is exactly why we should not anthropomorphise models.

You are comparing the way a human brain learn with training a statistical model. You can't just "this is like learning so don't be surprised".

It takes a child one minute to learn how to open a padlock. Teach that to a robot with your analogies.