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Show HN: I mapped HN's favorite books with GPT-4o

hnbooks.pieterma.es

41–50 of 65 posts

Re: Show HN: I mapped HN's favorite books with GPT-4o

#43

Niiice! I really like it. The spatial approach is cool, though labelling/annotations/axes would help. I share the frustraion with getting book covers for my project ablf.io. Amazon used to make this much easier, but they've locked it down recently, so you have to jump through affiliate hoops. I ended up implementing my own thing and storing thousands of images myself on S3. If you have the goodreads IDs, feel free to…

Nice site! I like that I can filter results by fiction or non-fiction. Interesting to enter my favourite novels and see the non-fiction that's recommended. Some surprisingly good picks!

Re: Show HN: I mapped HN's favorite books with GPT-4o

#46

Really cool to see my favs show up, but I honestly don't understand what we're actually looking at; the groupings seem very opaque beyond very general themes like sci-fi, startups, biographies, math, physics. In other words, what are the clustering shapes telling us? Can we dig in based on geography, publishing date, key terms or themes? Either way, I can't keep the site open for more than 30-40 seconds before it cra…

> Either way, I can't keep the site open for more than 30-40 seconds before it crashes. Yup, probably was about to happen to me too, had I not closed it. CPU fan almost launched off the troposphere about 30 seconds in. Probably a cluttered bunch of heavily unoptimized ReactJS modules in there (no offense to OP, I know it probably sped up development by 10x at least)

Nope, hug of death is seems:

Failed to load module script: Expected a JavaScript module script but the server responded with a MIME type of "text/html". Strict MIME type checking is enforced for module scripts per HTML spec.

Ad infinitum for a list of a couple .js files with repeating names.

Guess we'll have to come back in a day or two to experience it in it's full glory :).

Re: Show HN: I mapped HN's favorite books with GPT-4o

#48

Really cool to see my favs show up, but I honestly don't understand what we're actually looking at; the groupings seem very opaque beyond very general themes like sci-fi, startups, biographies, math, physics. In other words, what are the clustering shapes telling us? Can we dig in based on geography, publishing date, key terms or themes? Either way, I can't keep the site open for more than 30-40 seconds before it cra…

There's a sort of regular repeating confusion with embeddings that they're very well behaved in visual dimensions.

IMHO it's a category error that results from tutorials using the king + female = queen example (which, funnily enough, wasn't even true for the original word2vec, if commentary I've read previously here is correct).

Working with them a lot has me picture them more as "a multivariate function that outputs 768 numbers, and was learned by brute force" than "something that sees in 768 dimensions" --- of course, they're both true, but the second interpretation shades more than it illuminates once you're past the very first interrogatory of "so what is this calculating, exactly?"

Re: Show HN: I mapped HN's favorite books with GPT-4o

#50
Appreciate the work! I didn't find the value of reading until I broke up with my ex which had me rethinking about my whole life and value, that's how I found the value of reading, right now I read when commuting and sometimes I just don't know what to read next, this is a good place to find some good books, thanks!
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