>I imagine a research orientated GPT could keep going deeper and deeper until it hits the current limit of our understanding about a particular subject.

The problem is that you're kind of running up agains the limits of what the tech behind ChatGPT can do. It doesn't understand anything it's saying; it's just good at predicting what word should come next when it has lots of training data to go on. When you start talking about technical details that have maybe only been addressed in a few scientific publications, it takes some understanding of the meaning behind the words to assemble those details into a coherent summary; it can't be done based on language patterns alone. Even something like knowing which details are extraneous and which belong in a summary requires a large sample size to see which pieces of language are common to many sources and which are specific to one document. There's not enough training data for the deep dives you seek.

>Where I think a research assistant GPT would really shine is by being able to absorb all of these independent data points and instantly making the connections.

I think this is a great possibility for a research assistant AI eventually, but it will probably require advances in a different type of AI than the language models ChatGPT is using.