Comment by deepllm

As someone who's at a similar age and was interested in learning how to do this, there just aren't enough resources to do so. Most LLM research is in the form of academic papers, and there isn't any 'popular' way to learn these things, and besides that all said research assumes you have a B200 cluster ready to go. If you have weaker hardware (say an 8GB nVidia GPU, which is what I have) you're going to be limited to fine tuning small models or torturing yourself working the GPU for days per iteration trying to run things like https://github.com/karpathy/nanochat, which is hardly an educational experience. Renting cloud GPUs is expensive, and at this age the most I could muster up for experimentation is probably $100 or so, which only gets me 25 or so hours on a B200 which just isn't enough. So why would I bother myself with this if I'm already at a disadvantage because of not having access to the right hardware and when surely there are better ways to spend my time? I concluded the only way to learn and be competitive is by finding work at an AI lab somehow (not happening at 17), or studying ML at the right university.

Putting this in contrast with programming, I learned coding when I was 8, and it was incredibly stimulating to learn because you can quickly iterate and there were thousands of books and YouTube tutorials that dumb everything down and teach you fundamentals. All you needed was a $300 computer, and you can learn nearly anything you want, without being gatekept from this or that because you don't have enough vRAM / an sm_100 GPU.