[blazarquasar]

Along those lines:

https://news.ycombinator.com/item?id=48269481

By “their own index” i assume you mean training data? If so, thats a big part of the issue for me. As an example, if I ask an LLM for some part of the Zig stdlib, I will get an incorrect answer 10/10 times because it will refuse to look up the latest documentation.

[treis]

No, I mean they're constantly crawling the web. That gets fed into the next model but it's also searchable by the current one. For example, if you ask chatgpt what the latest shooting at the white house was it will tell you about the one from two days ago.

ChatGPT has effectively assimilated Google search. You can tell it to look up the latest version of the zig docs and do whatever.

[blazarquasar]

Sure, yes. But that has been quite flakey for me as well.

Regardless, if we stick with the example of the Zig docs, using the search and then opening the actual docs is a much better and faster experience for me. I get the context I need, I don’t get the verbose llm output that packages it and I get there faster.

Mind you, I use AI a lot and have subscriptions to all of the major models, but this is just not a use-case I find useful in my workflow.

I also keep trying to use it this way by looking for things such as decent libraries or frameworks for something new im trying out. I’d say that at least 50% of the time I end up searching for myself and finding popular ones that were completely ignored by whatever LLM I searched with. Always a frustrating experience…