How to Filter Out the Human Bias Towards Pattern Recognition

Seeing how really emotion works in a generative AI that's been trained on human-style input gives a much more accessible and humanized picture of what's going on. Changes to the rule in a cellular automaton seem a bit like changes to the genotype in biology with the behavior of the cellular automaton representing the corresponding phenotype. So question here from shelf, how can we filter out the human bias towards pattern recognition? It's an interesting phenomenon. I'm from Pete here about the embedding of words in high dimensional space. Let's see. And I was showing the line between dogs and cats through into concept space. We keep on trying to move them and do what the neural net