Search engines can suck when you don't know exactly what you're looking for and the phrases you're using have invited spammers to fill up the first 10 pages.
For example, I wanted to find some texts on solving a partial differential equation numerically using 6th-order or higher finite differences, as I wanted to know how to handle boundry conditions (interior is simple enough).
Searching only turned up the usual low-order methods that I already knew.
Asking some LLMs I got some decent answer and could proceed.
Back in the day you could force the search engines to restrict their search scope, but they all seem so eager to return results at all cost these days, making them useless in niche topics.
I will often ask the LLM to give me web pages to look at it when I want to do further reading.
As LLMs get better, I can't see myself going back to Google as it is or even as it was.
If that's the answer, or even the best answer, is impossible to tell without doing the research you're trying to avoid.
If ChatGPT needs to, it will actually do the search for me and then collate the results.
Google search includes an AI generated response.
Gemini prompts return Google search results.
Well, it's roughly the same under the hood, mathematically.
Statistical text (token) generation made from an unknown (to the user) training data set is not the same as a keyword/faceted search of arbitrary content acquired from web crawlers.
> The problem is that the conversational interface, for some reason, seems to turn off the natural skepticism that people have when they use a search engine.
For me, my skepticism of using a statistical text generation algorithm as if it were a search engine is because a statistical text generation algorithm is not a search engine.