@Axtremus said in Me Learning LLM Reasoning:
There probably is a lesson somewhere in this experience for multilingual LLM machine learning/reasoning, but I don’t know what that is yet.
Well, to me one obvious lesson is not about machine learning, but rather that, even if you’re very knowledgeable, you have relevant information, and your ideas are good, how you present it matters immensely. Being able to present complex information in an accessible way is the essence of good teaching.
I notice that video #1 says
High-level overview of reasoning in large language models, focusing on motivations, core ideas, and current limitations. No prior background is required.
But reading your comment makes me wonder if in fact prior background is needed… Because being able to present new ideas in an accessible to someone with no background in the subject is the essence of good presenting.
I’m curious about the subject matter in the video (for example, I want to hear about chain-of-thought prompting and chain-of-thought reasoning, and I want to know what they mean by in-context learning), but reading your post makes me hesitant to watch it…
