Trump er et godt eksempel på hvordan maskinlæring fungerer:
"Trump's algorithm is to say semi-random things until his crowd roars its approval, then he iteratively modifies those statements, seeking more and more approval, until he maxes out and tries a new tack.
This is one of the core strategies of machine-learning: random-walking to find a promising path, hill-climbing to optimize it, then de-optimizing in order to ensure that you haven't plateaued at a local maximum (think of how an ant tries various directions to find a food source, then lays down a chemical trail that other ants reinforce as they follow it, but some will diverge randomly so that other, richer/closer food sources aren't bypassed).
It also betrays one of the core problems with machine learning: bias in the sample-set. The people that Trump relies upon to give him his success feedback are the people who show up for Trump rallies, who are the most extreme, least-representative group of potential Trump voters. The more Trump optimizes for this limited group, the more he de-optimizes for the rest of the world."
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