alt Hacker NewsI think a lot of the problem with the current discourse is how black-and-white it is. Either you're a luddite or "ai pilled".
In most cases, LLMs can get you 80-95% of the way, sometimes less, sometimes more. And heck, sometimes, it just gets you somewhere wrong.
But it seems everyone is arguing about whether LLMs can be perfect software engineers in isolation running in a closet, and using that to say that LLMs do not have a massive potential in other scenarios.
Sometimes, I like to imagine how much more productive most organizations could be from the things that the internet gave us, even to this day. Most companies never really do even a fraction of what is possible. That helps to ground my view of LLMs as well.
The fault dear Brutus isn't in our language models, but in ourselves.
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>In most cases, LLMs can get you 80-95% of the way
On a tangent, this often gets misinterpreted as "LLMs reduce the time it takes to do the thing by 80-95%". That's not what it means.
>I think a lot of the problem with the current discourse is how black-and-white it is.
There is too much money involved for any rational debate.
> But it seems everyone is arguing about whether LLMs can be perfect software engineers
That's just those of us with longer memory holding the AI companies to the standards they declared themselves. Nobody forced Sam Altman to blab about a team of pocket PhDs, did they? I don't want the crap that does it correct 60℅ of the time - where is the god damn nation of PhDs in a datacemter already? Where is the AI doing all the SWE work "in 3-6 months"?
I think that's geohot's point as well. They're advocating against being fully "ai pilled". Saying we should be using AI as a tool, not for being a luddite.
I completely agree with your sentiment of “black or white.” I believe it comes from social media with primarily “radical” perspectives being the ones in the spotlight. Just not an environment that promotes nuance or friendly discussion
> In most cases, LLMs can get you 80-95% of the way, sometimes less, sometimes more.
That's my experience too, but it's 60-95% solutions in my case[1], with about 120-140% of lines of code required. I wish there was a harness that would let me mask code it should/n't change, because prompt-based refactors fail from the same over-eagerness.
1. I try faster, smaller models first.
LLMs can get you 80-95% of the way
But the big question is "where will '80-95% of the way' get you?"
Do you grind-out the last 5-20% in a period that's disappointingly long compared to the initial step? Or do you another 80% complete thing on top, and another and another until the whole structure collapses?
The post is talking about what groups might go what directions, which seems fair.
Yes, exactly, it's 'us' not the AI, which is great.
Why on earth would we ever remotely compare a 'tool' to 'a software engineer' ?
The 'great delusion' is not that 'AI can't code' - because obviously it can, and very well.
The problem is the 'anthropomorphism' and all this AGI nonsense.
If we called it 'Stochastic Mechanisms' and did not 'personalize' our prompts, refer to them as 'chat' or give them 'personalities' but remained in the domain of 'Stochastic Language CLI' ... then our metaphors would pbably not cloud our judgments.
Let the philosophers argue about AGI.
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It's funny, but the more I know about the true Luddites, the more I see their point of view.
" the original Luddites were primarily protesting against machinery used to "fraudulently and deceitfully" manufacture inferior goods, bypass labor standards, and strip skilled artisans of their livelihoods."