It's doing abstractive summarization over the search results, using GPT-3. The pipeline is: - Search using Google - Run some filters to exclude SEO spam,

It's doing abstractive summarization over the search results, using GPT-3. The pipeline is: - Search using Google - Run some filters to exclude SEO spam, etc. - Scrape the pages that are returned - Find chunks of text likely to align with the answer (comparing embeddings) - Feed the most likely chunks into GPT-3 to get a summary It is leveraging GPT-3 to produce better summaries, and it isn't purely extractive - the LLM uses context and knowledge to generate a better summary. I want to experiment with a local model next, versus using GPT-3.