Comment by golfer

If you want to really test this, search/replace the names with your own random ones and see if it lists those.

Otherwise, LLMs have most of the books memorised anyway: https://arstechnica.com/features/2025/06/study-metas-llama-3...

I think the OP was implying that it's probably already baked into its training data. No need to search the web for that.

This underestimates how much of the Internet is actually compressed into and is an integral part of the model's weights. Gemini 2.5 can recite the first Harry Potter book verbatim for over 75% of the book.

Do the same experiment in the Claude web UI. And explicitly turn web searches off. It got almost all of them for me over a couple of prompts. That stuff is already in its training data.

The only worthwhile version of this test involves previously unseen data that could not have been in the training set. Otherwise the results could be inaccurate to the point of harmful.

I'm not sure what your knowledge level of the inner workings of LLMs is, but a model doesn't need search or even an internet connection to "know" the information if it's in its training dataset. In your example, it's almost guaranteed that the LLM isn't searching books - it's just referencing one of the hundreds of lists of those spells in it's training data.

This is the LLM's magic trick that has everyone fooled into thinking they're intelligent - it can very convincingly cosplay an intelligent being by parroting an intelligent being's output. This is equivalent to making a recording of Elvis, playing it back, and believing that Elvis is actually alive inside of the playback device. And let's face it, if a time traveler brought a modern music playback device back hundreds of years and showed it to everyone, they WOULD think that. Why? Because they have not become accustomed to the technology and have no concept of how it could work. The same is true of LLMs - the technology was thrust on society so quickly that there was no time for people to adjust and understand its inner workings, so most people think it's actually doing something akin to intelligence. The truth is it's just as far from intelligence your music playback device is from having Elvis inside of it.

Honestly? My advice would be to cook something custom up! You don't need to do all the text yourself. Maybe have AI spew out a bunch of text, or take obscure existing text and insert hidden phrases here or there.

Shoot, I'd even go so far as to write a script that takes in a bunch of text, reorganizes sentences, and outputs them in a random order with the secrets. Kind of like a "Where's Waldo?", but for text

Just a few casual thoughts.

I'm actually thinking about coming up with some interesting coding exercises that I can run across all models. I know we already have benchmarks, however some of the recent work I've done has really shown huge weak points in every model I've run them on.