Feeding the machine: We give an AI some headlines and see what it does

Turning the lens on ourselves, as it were.

Amplify / Turning the lens on ourselves, because it have been.

There is a second in any foray into new technological territory while you notice you will have launched into a Sisyphean process. Staring on the multitude of choices to be had to take at the venture, you analysis your choices, learn the documentation, and begin to paintings—most effective to search out that in fact simply defining the issue could also be extra paintings than discovering the real answer.

Reader, that is the place I discovered myself two weeks into this journey in mechanical device studying. I familiarized myself with the knowledge, the equipment, and the recognized approaches to issues of this sort of knowledge, and I attempted a number of approaches to fixing what at the floor appeared to be a easy machine-learning downside: in response to previous efficiency, may we think whether or not any given Ars headline will probably be a winner in an A/B take a look at?

Issues have now not been going specifically smartly. In reality, as I stopped this piece, my most up-to-date try confirmed that our set of rules used to be about as correct as a coin turn.

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