4 ms·
I think they are right. Advanced ML requires both IQ and career dedication. Doing say the intro YT series building yoyr own LLM and understanding and sucessfull
by nrnrjrjrj 2y ago
I think they are right. Advanced ML requires both IQ and career dedication. Doing say the intro YT series building yoyr own LLM and understanding and sucessfully using PyTorch data strucutres in 3 even 4 dimensional (as in an array of array of array of arrays) doing matrix algebra...
I would say this gets possible at 120 and only easy at 140 at a guess.
Edit: i am serious
- calebkaiser 2y agoAnecdotally, as part of my job, I've taught ML concepts to a lot of people. I don't know if I've ever worked with anyone who was simply too "unintelligent" to grasp things. The bottleneck, as for most things in my experience, is time and motivation. In any niche of ML, there's just a lot of things to learn, particularly if you aren't starting with a particularly math-y background.
- deleted 2y ago[deleted]
- hilux 2y agoYou were probably working at a fairly advanced tech company. As were the people you were teaching. If by "ML concepts" you mean "how to implement ML" - do you really think that people who got to a job that required learning this, represent the population IQ distribution?
- jdjdnndn 2y agoI cannot tell if you are serious.