Source New! Listen to a 10min autogenerated podcast discussing this blogpost from Google LLM Notebook Ex Libris surprised us by suddenly releasing Primo Research Assistant to production on September 9, 2024  (when the earlier timeline was 4Q 2024 with some believing it might even be delayed). Despite the fact that there are so many RAG (retrieval augmented generation) academic search systems today that

New! Listen to a 10min autogenerated podcast discussing this blogpost from Google LLM Notebook Update Primo Research Assistant is out - See my initial preliminary view IP and ethical issues surrounding the use of content in Large Language Models (LLMs) have sparked significant debate, but I’ve mostly stayed out of it as this isn’t my area of expertise, and while there’s much to discuss and many legal opinions to

New!  Listen to a 7 min autogenerated podcast discussing this blogpost from Google LLM Notebook I recently watched a librarian give a talk about their experiments teaching prompt engineering.

New! Listen to a 10min autogenerated podcast discussing this blogpost from Google LLM Notebook I have been writing about what I call citation based literature mapping tools for over 5 years now, starting from Citation Gecko in 2018.

Can Semantic Search be more interpretable?

Warning : I am not a information retrieval researcher, so take my blog post with a pinch of salt In my last blog post, I described a simplified description of a framework for infomation retrieval from the paper -

As academic search engines and databases incorporate the use of generative AI into their systems, an important concept that all librarian should grasp is that of retrieval augmented generation (RAG).   You see it in use in all sorts of "AI products" today from chatbots like Bing Copilot, to Adobe's Acrobat Ai assistant that allow you to chat with your PDF.

Let's be clear here, Google Scholar is ill designed for use for systematic reviews . I am not trying to argue otherwise. (Obligatory warning, I am not a real systematic review librarian) But why exactly?

EDIT - April 2025 Since I wrote this blog post in April 2024, "Deep Research" tools have become all the rage, that combine agentic search and producing long form reports are now all the rage. New: See updated Oct 2024 review of Undermind here!

I've watched with interest, as academic search engines use AI to improve searching.  Elicit is probably currently the leading example of this, using transformer based language models to  improve search relevancy ranking  use RAG (retrieval augmented generation) across multiple documents to generate a paragraph of text to answer the query with citations extract information to create a research matrix table of papers

One of the tricks about using the newer "AI powered" search systems like Elicit, SciSpace and even JSTOR experiment search is that they recommend that you type in your query or what you want in full natural language and not keyword search style (where you drop the stop words) for better results. So for example do