Resonant – discover and search high quality blogs

Hey HN, Blog discovery is a problem [0] due to the decentralized nature of online writing. Everyone writes on their own site or platform, and there’s no central place that brings everything together. Google results prioritize large media publications over blogs, so we need something else. Blog Surf is an attempt to organize all of the great online writing done by individuals. I launched this project last year as a directory of personal blogs [1], but have now rebuilt it from scratch into a full-text search engine for blog posts. You can search for blog posts, and filter by publish date and…

Discover great blogs lost in your Twitter timeline

We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by…

Hey HN, maker here. It was a serious 4-6 months of effort to build this. I have never poured as much love, attention and detail into a project before. So I really appreciate you having a looksie! The homepage has a fresh list of articles every hour and is open to all. Still, I recommend signing up so you can add stuff to your reading list and follow blogs. My initial plan was to monetize this with subtle ads, but that didn't work out as the traffic to the site isn't nearly enough for that. That said, I have a fair bit invested in this and I need your help figuring out a way to make this…

We built a search engine that shows you the most engaging stories/topics being shared across Twitter, Facebook, Linkedin, and Google+. We crawled over 15 million articles the past 3 months, retrieved the total number of Facebook likes, tweets, Google+’s etc and built a search index around it. Here's what our infrastructure looks like: Rails/Redis: We use the Sidekiq gem as a message queue. We have hundreds of workers that do the crawling, data mining, and number crunching. ElasticSearch: We built the search index using ElasticSearch, with the data imported from our Postgres…