An analysis of the quality of AI-generated summaries of a technical paper, comparing outputs from Gemini, ChatGPT, Claude, Grok, Perplexity, and NotebookLM. The author finds Gemini to be the best, highlighting the importance of context in prompting and the potential usefulness of AI summaries as 'extended abstracts'.
This article explores the use of Google's NotebookLM (NLM) as a tool for research, particularly in analyzing the impact of the Aswan High Dam on schistosomiasis in Egypt. The author details how NLM can be used to create a research assistant-like experience, allowing users to 'have a conversation' with uploaded content to gain insights and answers from the material.
