Comment by fancyfredbot
14 hours ago
I'm (more than) twice that age, but I've spent time learning this exactly this from videos by Andrej Karparthy and from books by Sebastian Raschka.
I didn't do it because it was useful to me in a practical sense. It's because LLMs are fascinating and I want to know how they work. From that perspective it's been a great experience. I have afirm grasp of the basics. This makes it much easier to understand frontier concepts like compressed latent attention. I can follow the field and understand it.
Not sure I would have got as much out of it at seventeen. I have a lot of background and experience which made it much easier to learn. I wasn't struggling with the linear algebra or with python. I already knew pytorch and neural networks. That helped a lot and I covered these tutorials fast and could skip over large sections. A few evenings and the odd weekend day over a couple of months was enough for me.
For seventeen year olds the tutorials are good enough to make it possible to learn this but it would have taken a lot longer to understand. On the other hand I would have learned a lot more. I think I would have learned a lot of valuable stuff.
However I also think 17 year old me was studying for his A levels and probably this was right choice in terms of maximising future opportunities. I'm not sure I think learning about LLMs instead is sensible. Indeed it might be bad advice. But I can absolutely agree with the sentiment.I think 17 year old me would have wanted to do this too.
Which resources from these two would you recommend? Or just blanket-recommend all their videos/books?
I kind of want to blanket recommend but that's not very helpful
I would suggest starting with Andrej Karpathy's YouTube video: https://youtu.be/kCc8FmEb1nY?is=oiDsrBYJg_MUUmoD
This video is excellent. I'm a huge fan. Also the video is zero commitment and instantly available which makes it a good way to check you are interested.
The book by Sebastian Raschka is slightly less accessible but very reasonably priced and the experience of working through a book is a lot nicer than skipping back and forth in a video (for me). Sebastian's blog posts on recent architectures are absolutely great too.
I've read Raschka's "Build Your Own LLM from Scratch" book and really enjoyed it. I haven't tried the code yet, but the code from his previous Python ML book worked great.
actually just use chatgpt. There is a new mode of learning thats now avaiable that doesnt require you to read about things that are already discovered leaving you with a shallow knowledge.
you can now play the inventor and start with question "i want to build next token prediction software" and go as far as you can with your current knowledge while brainstroming with chatgpt as a rubber duck.
dont not start with a course on probabality , linear algebra or calculus . do not watch 3 hr videos or 3blue animations .
there is agood video on this way to learn.
https://www.youtube.com/watch?v=cbiyPOn-__M&t=380s
I think ChatGPT is a great way to get depth on a topic. You can Q&A for a while until you get it, and it won’t get impatient with you.
That said, I think traditional resources are a better way to get breadth and to frame the topic. Just chatting about something can be a little disorienting imo.
so can u explain to me how they are works?