Having said that - the tradeoff with getting into a new field is that there is 50 years of history to dig through, and by the time you know exactly what you’re looking for, you don’t need to find it really. Although a better math framework or another approach would help a bit for sure.
I think in the future it will be way easier with better llm searches. Gpt right now fell short in finding some stuff, but it was already very useful in giving me an overview of the field.
Also, awesome job! Thanks for writing up some seriously cool engineering.
The modern patent system in a nutshell. It's now suits registering patents rather than inventors in their workshops.
While working, I kept asking it about certain ideas, and if the idea was known to him, he said "oh, that's this and it's called this and this".
As a fun sidenote, I noticed there are three levels of GPT's answers: - "This has a name and it's...." - "This will be difficult / very hard to do..." (it will never say impossible) - "This is an intriguing idea"
The last one is what one should aim for - I noticed that when it sees an idea that is absolutely new to it, but it doesn't see any specific reason it should not be possible, it will label it as "intriguing".
The topmost compliment I got, when asked about opinion it said more or less "it shows a deep and nuanced understanding of XX, you should publish" (and then began listing steps necessary - testing, finding collabolators etc).
All in all GPT was super useful for getting into a new field - I didn't want to reinvent the wheel, but I didn't want to spend months catching up with the 50 years history of this field. I kept repeatedly asking him for stuff like "I need to do this and this", and it kept pointing me in the right directions and providing nomenclature.
If you didn't find these works in your literature search, I encourage you to improve this skill, because it's important and valuable.