alt Hacker NewsWhat meaningful connections did it uncover?
You have an interesting idea here, but looking over the LLM output, it's not clear what these "connections" actually mean, or if they mean anything at all.
Feeding a dataset into an LLM and getting it to output something is rather trivial. How is this particular output insightful or helpful? What specific connections gave you, the author, new insight into these works?
You correctly, and importantly point out that "LLMs are overused to summarise and underused to help us read deeper", but you published the LLM summary without explaining how the LLM helped you read deeper.
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I like design that highlights words in one summary and links them to highlights in the next. It's a cool idea
But so many of the links just don't make sense, as several comments have pointed out. Are these actually supposed to represent connections between books, or is it just a random visual effect that's suppose to imply they're connected?
I clicked on one category and it has "Us/Them" linked to "fictions" in the next summary. I get that it's supposed to imply some relationship but I can't parse the relationships
100 books is too small a datasize - particularly given it's a set of HN recommendations (i.e. a very narrow and specific subset of books). A larger set would probably draw more surprising and interesting groupings.
The connections are meaningful to me in so far as they get me thinking about the topics, another lens to look at these books through. It's a fine balance between being trivial and being so out there that it seems arbitrary.
A trail that hits that balance well IMO is https://trails.pieterma.es/trail/pacemaker-principle/. I find the system theory topics the most interesting. In this one, I like how it pulled in a section from Kitchen Confidential in between oil trade bottlenecks and software team constraints to illustrate the general principle.