When a person reads a book, they have an "overall intuition" about it. We need some way to quantify this. Needle in haystack tests feel like a simple test that doesn't go far enough.
Generate 1000 generic facts about Alice and the same 1000 facts about Eve. Randomise the order and change one minor detail then ask how they differ.
sort alice.txt | diff - <(sort eve.txt)
The idea presented elsewhere in this thread about using an unpublished novel and then asking questions about the plot is sort of the ideal test in this regard, and clearly on the other end of the spectrum in terms of a design that's testing actual "understanding".
A useful test would copy all Alice statements to Eve statements, then rewrite all of the Eve statements using synonyms, and then finally change one or two details for Eve.
This whole thing would have to be kept under lock-and-key in order to be useful, so it would only serve as a kind of personal benchmark. Or it could possibly be a prestige award that is valued for its conclusions and not for its ability to use the methodology to create improvements in the field.
GPT4o still can't do the intersection of two different ideas that are not in the training set. It can't even produce random variations on the intersection of two different ideas.
Further though, we shouldn't expect the model to do this. It is not fair to the model and its actual usefulness and how amazing what the models can do with zero understanding. To believe the model understands is to fool yourself.
I am many years out of my grade school years where I was required to read a multitude of novels every year and I guess years of mindless reddit scrolling + focusing on nothing but mathematics and the sciences in college have taken their toll: I read long articles or books but completely miss the deeper meaning.
As an example: my nerd like obsession with random topics of the decade before I was born (until I get bored) caused me to read numerous articles and all of Wikipedia + sources on the RBMK reactors and Chernobyl nuclear accident as well as the stories of the people involved.
But it wasn't until I sat down and watched that famous HBO mini seres that I finally connected the dots of how the lies and secretive nature of the soviet system led to the design flaws in the reactor, and the subsequent suicide of Valery Legasov helped finally expose them to the world where they could no longer be hidden.
Its like I knew of all these events and people separately but could not connect them together to form a deep realization and when I saw it acted out on screen it all finally hit me like a ton of bricks. How had I not seen it?
Hoping one day AI can just scan my existing brain structure and recommend activities to change the neuronal makeup to what I want it to be. Or even better since im a lazy developer, it should just do it for me.
It's hard, but if you have a piece of fiction or non-fiction it hasn't seen before, then a deep reading comprehension question can be a good indicator. But you need to be able to separate a true answer from BS.
"What does this work says about our culture? Support your answer with direct quotes."
I found both gpt-4 and haiku to do alright at this, but sometimes give answers that imply fixating on certain sections of a 20,000 k context. You could compare it against chunking the text, getting the answer for each chunk and combining them.
I suspect if you do that then the chunking would win for things that are found in many chunks, like the work is heavy handed on a theme, but the large context would be better for a sublter message, except sometimes it would miss it altogether and think a Fight Club screenplay was a dark comedy.
Interpretation is hard I guess.