I built this tool to help me find interesting discussions on Hacker News. I love reading HN discussions almost more than the articles themselves. However, I found that full text search, although highly performant, is not always good at surfacing interesting discussions on a certain topic -- especially if you don't know what to search for exactly.
I built this by scraping the most recent ~6 million posts (that's about 2 years of history) and putting the resulting posts and their vector embeddings into Postgres.
Let me know what could be improved, and if you'd like a more detailed writeup of how this was built :)
Three of examples on the current home page surface some toxic threads (“llm waifus”, “internet of shit”, and “AI Doomers”)… which while controversial aren’t as rich or insightful as say the comments from people that built Rust, the whole earth catalog, or the first x86 chip.
[1] https://news.ycombinator.com/bestcomments