I've tried Adobe Acrobat AI for this and it doesn't work yet. NotebookLM is it. The grounding is the reason it works - you can easily click on anything and it will take you to the source to verify it. My only gripe is that the visual display of the source material is _dogshit ugly_, like exceptionally so. Big blog pink background letters in lines of 24 characters! :) It has trouble displaying PDF columns, but at least it parses them. The ugly will change I'm sure :)
My projects are setup to let me bridge the gaps between the various sources and synthesize something more. It helps to have a goal and organize your sources around that. If you aren't focused, it gets confused. You lay the groundwork in sources and it helps you reason. It works so well I feel _tender_ towards it :) Survey papers provide background then you add specific sources in your area of focus. You can write a profile for how you would like NotebookLM to think - which REALLY helps out.
They are:
* The Stratigrapher - A Lovecraftian short story about the world's first city. All of Seton Lloyd/Faud Safar's work on Eridu. Various sources on Sumerian culture and religion All of Lovecraft's work and letters. Various sources about opium Some articles about nonlinear geometries
* FPGA Accelerated Graph Analytics An introduction to Verilog Papers on FPGAs and graph analytics Papers on Apache Spark architecture Papers on GraphFrames and a related rant I created about it and graph DBs A source on Spark-RAPIDS Papers on subgraph matching, graphlets, network motifs Papers on random graph models
* Graph machine learning notebook without a specific goal, which has been less successful. It helps to have a goal for the project. It got confused by how broad my sources were.
I would LOVE to share my projects with you all, but you can only share within a Google Workspaces domain. It will be AWESOME when they open this thing up :)