lvxferre@lemmy.ml
on 18 Nov 2023 03:18
nextcollapse
Given that it’s pointing straight to “no”, should I interpret “AI” as “additional irony”?
…seriously, model-based generation is in its infancy. Currently it outputs mostly trash; you need to spend quite a bit of time to sort something useful out of it. If anyone here actually believes that it’s smart, I have a bridge to sell you.
But 99% accuracy is better than any human alive, so while maybe LLMs won’t be able to substitute critical systems, they might just replace all the people around those systems.
Like, we won’t want an AI as the failsafe for a nuclear plant. But we might prefer an AI as the the “person” in charge of this failsafe.
Current generations aren’t even close to that rate, and it’s unclear if it’s economical or even possible to fix the deep structural issues of our current Gen LLMs.
My professional experience with LLMs is that they don’t even approach 20% accuracy for a field as ridiculously structured as programming.
They’re just helpful enough to not be a hindrance.
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Data privacy concerns, data privay concerns, data priacy coucerns, and data apiacy concext!
I love how the question “should I use AI?” points directly to no.
It also ponys directly to Yes es?
Given that it’s pointing straight to “no”, should I interpret “AI” as “additional irony”?
…seriously, model-based generation is in its infancy. Currently it outputs mostly trash; you need to spend quite a bit of time to sort something useful out of it. If anyone here actually believes that it’s smart, I have a bridge to sell you.
LLMs will undoubtedly improve as we build more systems around them.
The question is will it ever be reliable enough to trust? You can’t have a 99% reliable critical system.
But 99% accuracy is better than any human alive, so while maybe LLMs won’t be able to substitute critical systems, they might just replace all the people around those systems.
Like, we won’t want an AI as the failsafe for a nuclear plant. But we might prefer an AI as the the “person” in charge of this failsafe.
Current generations aren’t even close to that rate, and it’s unclear if it’s economical or even possible to fix the deep structural issues of our current Gen LLMs.
My professional experience with LLMs is that they don’t even approach 20% accuracy for a field as ridiculously structured as programming.
They’re just helpful enough to not be a hindrance.
Not too mention plenty of humans are 99% accurate
Topical:
arstechnica.com/…/ai-with-90-error-rate-forces-el…
I require humarmip in cons cunt
“cons cunt” is just Aussie slang for Lisp Programmer.
You are a genius
the task is clearly repeisitive
Fuck Jeff Atwood
Why?
If you’ve ever had an interaction with him, you’d know why