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> The title is transformed it into an array of numbers between 0 and 1 (each character is a number) and this data is fed (along with the number of points) to the neural network.

This sounds strange. But after looking at the authors bio, it isn't strange any more. This has less to do with AI and more with cheap growth hacking.

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It's also strange because what they've trained is essentially a recommender system. However, at inference time you're not trying to rank 2 different articles, but the same article with 2 different titles, which I guess you could do, but I'm not sure how well this correlates to your actual ranking on HN.

I guess something more interesting would be to take into account the current front page and see how your article would rank against those, or something along these lines.

In any case, neat idea.

Yeah, this is a classic case GIGO.

> Title A: kdjfs;dfisd;diofuosd

> Title B: sdlkn nmkd kljdsa;'[ (10% better)

> The winner is title B: sdlkn nmkd kljdsa;'[

I had to look up GIGO; "Garbage in, garbage out", https://en.wikipedia.org/wiki/Garbage_in,_garbage_out .

Converting text to numbers via individual characters destroys any semantic meaning to the input. Which is why no advanced NLP tools will do such a thing. Basically, what they describe takes whatever meaning is in the title and throws it in a shredder.

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