SearchResearch Challenge (1/10/24): What's the best direction for SRS?

It’s a New Year!

P/C Dalle3. [an evocative picture of data, data tables, line charts, histograms]

Let’s reflect on what SearchResearch is all about…

I started this blog back in January, 2010 with About this blog–Why SearchReSearch? That was 5,093 days ago.

So far, there has been 1,374 posts, with 4.75M views and 13,700 comments. We’re running around 40K blog views / month, and that doesn’t include the various syndicated versions of the blog. If you include those, I’m Fermi Estimating the readership at 50K /month. That’s a decent number (roughly 1,660 people / day).

As longtime SRS readers know, one of my goals was to use the blog as an effective prompt to write a book. That book–The Joy of Search: A Google Insider’s Guide to Going Beyond the Basics—came out in September 2019 and has done reasonably well. At least well enough to be translated into Korean and Chinese, as well as go into a paperback edition.

As my Regular Readers also know, I’m working on another book (“Unanticipated Consequences”) which I’m trying to finish up in the first part of this year, 2024.

Writing a regular blog is a serious investment of time and energy, at least it is for me. On average, I spend around 4-8 hours each week bringing you the most interesting SearchResearch tidbits I can find.

But it’s a big time commitment, and I’d like to use those hours to work on the new book.

So I’m going to try an experiment–scaling back a bit, trying to do each blog post in two hours or less.

To do that, I’m going to try to involve you Regular Readers a bit more in the search for insights.

As we’ve discussed, the advent of Generative AI is promising to radically change the SearchResearch process. It has the ability to give us new insights quickly (an example), and also to generate convincing-sounding nonsense with ease (an example).

I know that many of you are using ChatGPT or Bard or Llama to answer questions, so I want to tap into the collective intelligence that SRS Regular Readers can bring to the discussion.

I’ve asked this before in general (How can we use LLMs to search even better?) and for the specific case of medical searches (How might we best use LLMs for online medical research?). But if there’s one thing to know about LLMs and Generative AI in general, it’s that this field is changing fast–really fast–fast as a flash rifling down the electric blue gun barrel into a sea of new-age synth-pop psychedelia.

So…

Our SearchResearch Challenge of the week is this is to revisit this:

1. How have you found yourself using an LLM system (or more generally, any GenAI system) to help solve a real SearchResearch question that you’ve had?

I’ve told you before that I’ve used ChatGPT to help me with some data table manipulation. I’ve solved a few problems in a minute that would have taken me an hour or more to do with my regular programming skills. Those are huge savings.

I’ve also gotten LLM help in finding answers to SRS questions that I couldn’t figure out how to frame as a “regular” Google search. Bard has answered a couple such questions for me (which I then fact-checked immediately!).

We all want to know what you’ve found to be useful. What has worked for you in the past few months?

Alternatively, what has NOT worked out for you?

We’re all ears here at SRS!

Keep searching.