Since I am not in the AI industry, I think I do not understand few things:
- what is RL? Research Language?
- does it mean that in essence AI companies will switch to writing enterprise software using LLMs integrated with enterprise tools?
[EDIT] Seems like you can even ask a question on HN because 'how dare you not know something?' and gonna be downvoted.
* RL is Reinforcement Learning. Already used for a while as part of RLHF but now we have started to find a very nice combo of reasoning+RL on verifiable tasks. Core idea is that models are not just good a predicting the next token but the next right answer.
* I think anything infra with already some ML bundled is especially up for grabs but this will have a more transformative impact than your usual SaaS. Network engineering is a good example: highly formalized but also highly complex. RL models could increasingly nail that.
What is RLHF?
As an author, you should care about reducing friction and decreasing the cost to the reader.
No. And yet... it's considered a Good Practice to expand acronyms on first use, and generally do things to reduce the friction for your audience to understand what you're writing.
Sure, if you're writing a blogpost titled "Architecture for Chefs" then yes, write with that audience in mind.
But we're a mix-match of folks here, from all different walks of life. Requiring that everyone should expand all acronyms others possibly might not understand, would just be a waste of time.
If I see two cooks discussing knives with terms I don't understand, is it really their responsibility to make sure I understand it, although I'm just a passive observer, and I posses the skill to look up things myself?
Exactly!
Why would I waste 5 seconds of my own time, when I could waste 5 seconds of a dozen to hundreds of people's time?
My time is much better spent in meta-discussions, informing people that writing out a word one single time instead of typing up the acronym is too much.