Regic · HackerTrans

I feel like the fact that ML has no good explanation why it works this well gives a lot of people room to invent their head-canon, usually from their field of expertise. I've seen this from exceptionally intelligent individuals too. If you only have a hammer...

Regic

2 jaar geledendiscuss

Don't we all experience this from time to time? When I'm focused on solving some mathematical problems I'm not thinking in words, but in concepts. When you are thinking of words you also think of a concept, the only difference is that sometimes there are no words associated to it. Im my opinion, words, sentences are just a label to the thinking process, a translation of what is really going on inside, not the driver of it.

Regic

2 jaar geledendiscuss

This exists and does work to some degree, e.g. Detecting hallucinations in large language models using semantic entropy https://www.nature.com/articles/s41586-024-07421-0

Regic

2 jaar geledendiscuss

My experience is mostly with gpt-4. Act like it is a beginner programmer. Give it small, self-contained tasks, explain the possible problems, limitation of the environment you are working with, possible hurdles, suggest api functions or language features to use (it really likes to forget there is a specific function that does half of what you need instead of having to staple multiple ones together). Try it for different tasks, you will get a feel what it excels in and what it won't be able to solve. If it doesn't give good answer after 2 or 3 attempts, just write it yourself and move on, giving feedback barely works in my experience.

Regic

3 jaar geledendiscuss

> There were a lot of people who were just reciting the best practice rules they'd learned from blog posts, without really having the experience to know where the advice was coming from, or how best to apply it

This is exactly my experience too. Also, the problem with learning things from youtube and blogs is that whatever the author decides to cover is what we end up knowing, but they never intended to give a comprehensive lecture about these topics. The result is people who dogmatically apply some principles and entirely ignore others - neither of those really work. (I'm also guilty of this in ML topics.)

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