I disagree. Machine Learning is just super-charged linear regression.
If you build a ML system that autonomously chooses it factors, and automatically adjusts to model drift (by either adjusting existing coefficients (easy) or adding/removing factors (hard), then ML drifts into AI.
> I disagree. Machine Learning is just super-charged linear regression.
Machine learning is neural nets, which started out as an approach to AI and which yes boil down to linear regression, but that's about as useful as saying brains are just super super charged linear regression. And that's the point, AI is a label that keeps getting cast off of things that started out as AI but once understood people decided they no longer were, you are committing the no true Scotsman fallacy. If it started off as AI, it's AI, that doesn't change because you understand the math underneath that it boils down to.
I disagree. Machine Learning is just super-charged linear regression.
If you build a ML system that autonomously chooses it factors, and automatically adjusts to model drift (by either adjusting existing coefficients (easy) or adding/removing factors (hard), then ML drifts into AI.