[in-silico]

> Current AI systems can give best guess statistical answer from dataset the've been fed.

What about reinforcement learning? RL models don't train on an existing dataset, they try their own solutions and learn from feedback.

RL models can definitely "invent" new things. Here's an example where they design novel molecules that bind with a protein: https://academic.oup.com/bioinformatics/article/39/4/btad157...

[omnimus]

Finding variations in constrained haystack with measurable defined results is what machine learning has always been good at. Tracing most efficient Trackmania route is impressive and the resulting route might be original as in human would never come up with it. But is it actually novel in creative, critical way? Isn't it simply computational brute force? How big that force would have to be in physical or less constrained world?