It is getting doubly weird with the LLM/Diffusion explosion over the last year. The applied research ML role has evolved from being a computational math role t

It is getting doubly weird with the LLM/Diffusion explosion over the last year. The applied research ML role has evolved from being a computational math role to a Pytorch role to a 'informed throw things at the wall' role. I went from reading textbooks (Murphy, Ian Goodfellow, Bishop) to watching curated NIPS talks to reading Axriv papers to literally trawling random discord channels and subreddits to get a few month leg up on anyone in research. Recently, a paper formally cited /r/localllama for their core idea. > follow online tutorials The Open Source movement moves so quickly, that running someone's collab notebook is the way to be at the cutting edge of research. The entire agents, task planning and meta-prompting field was invented in random forums. ________________ This is mostly relevant to the NLP/Vision world......but take a break for 1-2 years, and your entire skill set is obsolete.