Hi HN - it's been getting hard for me to do research with Google. If I'm looking for the best smartphone, or the right Javascript framework, I have to wade through dozens of SEO-spam pages to find the answer.<p>I've experimented with different solutions to this - Kagi, DDG, SearX, and writing my own custom filters. Nothing quite works the way I want.<p>Last weekend, I decided to feed text from Google search results into GPT-3 to generate summaries with citations. This works well - I get an overview of the topic, but also dive deeper if I need to by clicking on the citations. Citations help verify the information and ensure accuracy (I've noticed fewer hallucinations than with GPT-3 alone).<p>It works by getting results from Google, scraping the pages, extracting text chunks that align with the question (using embeddings), then sending the most aligned chunks to GPT-3. The GPT-3 prompt specifies to only use the chunks to generate the answer (this usually works).<p>Since it's self-hostable, it's easy to tune and hack to suit your preferences.