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by malux85 1007 days ago
Yes, created by hand, lots of techniques are required to get a well running system, GoT (graph of thought) RAG (retrieval augmented generation), Ko detection, dynamic problem decomposition, and a few more techniques I have invented but dont really have names for. Its also quite a bit more complicated than the simplistic answer I gave before because you have to do things like experiments in abstraction laddering to get good interface composability.

This space is moving so quick I run many experiments every day.

I would love to work on this full time, I applied to y-combinator but I didn't get in :(

3 comments

Random question for you: How feasible is it for someone with a software/ML background to get into this space? I'd like to get into learning a new domain through ML, but it feels very daunting.
It sounds cliche but the old advice “do something you’re passionate about” applies. I have loved chemistry since I was a teenager because I had an inspiring teacher, without this passion I would have given up when I got to the very hard parts of math.

Personally I had to level up my math game a lot, when I started I had to keep pausing looking up terms, then write tiny prototypes, then keep learning. At the start it took me a month to read and understand a paper, now I can skim read them in minutes, without a passion for chemistry and the self discipline to keep at it I would have given up.

Take extensive notes, actually review them frequently, and refractor them as you learn.

Find mentors in the space, while reading papers I took names and reached out, I offered free programming to anyone who I found inspiring, and this built relationships with some pretty amazing professors and students around the world.

Hope that helps! <3

That’s too bad, did YC give you a reason?
YC doesn't give reasons.