Deep Dive
Like NotebookLM, but pointed at my own content: the podcasts I follow and any YouTube video I throw at it. It reads everything, hands back one consolidated take, then lets me ask questions to go deeper.
It runs on the home server, so there's no public instance, but I'm happy to give you a tour.
What it does
I get through a lot of podcasts and the odd long YouTube video, and the good bits never stick the first time round. This pulls a week's worth of that content into one place, writes a single consolidated analysis across all of it, and then lets me sit and talk to it (“what was the argument about X?”, “how does this connect to last week?”) until I actually understand the thing.
It's basically NotebookLM for my own feeds: same idea of grounding the model in a set of sources I chose, but built around the podcasts and videos I already follow rather than documents I have to upload.
How it works
Each source, whether a podcast feed or a YouTube link, gets transcribed and chunked into a vector store. When I start a session, the relevant passages are retrieved and a language model writes the consolidated summary, then answers follow-ups using only those sources, so the conversation stays anchored to what was actually said.
Sessions and bookmarks are saved, so I can come back to a topic later and keep pulling on the thread.