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- cross-posted to:
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Yeah, had that on my very first attempt at using it.
It used a component that didn’t exist. I called it out and it went “you are correct, that was removed in <older version>. Try this instead.” and created an entirely new set of bogus components and functions. This cycle continued until I gave up. It knows what code looks like, and what the excuses look like and that’s about it. There’s zero understanding.
It’s probably great if you’re doing some common homework (Javascript Fibonacci sequence or something) or menial task, but for anything that might reach the edges of its “knowledge”, it has no idea where those edges may lie so just bullshits.
Lie… no hallucinate…they lie and make shit up… just like a real hooman!! :))
Can we fucking stop anthropomorphising software?
“Hallucinate” is the standard term used to explain the GenAI models coming up with untrue statements
in terms of communication utility, it’s also a very accurate term.
when WE hallucinate, it’s because our internal predictive models are flying off the rails filling in the blanks based on assumptions rather than referencing concrete sensory information and generating results that conflict with reality.
when AIs hallucinate, it’s due to its predictive model generating results that do not align with reality because it instead flew off the rails presuming what was calculated to be likely to exist rather than referencing positively certain information.
it’s the same song, but played on a different instrument.
when WE hallucinate, it’s because our internal predictive models are flying off the rails filling in the blanks based on assumptions rather than referencing concrete sensory information and generating results that conflict with reality.
Is it really? You make it sound like this is a proven fact.
Is it really? You make it sound like this is a proven fact.
I believe that’s where the scientific community is moving towards, based on watching this Kyle Hill video.
Here is an alternative Piped link(s):
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I’m open-source; check me out at GitHub.
I know I’m responding to a bot, but… how does a PipedLinkBot get “Kyle Hill” wrong to “Kyke Hill”? More AI hallucinations?
Op has a pencil in the top right, looks like it was edited
What standard is that? I’d like a reference.
It’s as much as “Hallucination” as Tesla’s Autopilot is an Autopilot
https://en.m.wikipedia.org/wiki/Tesla_Autopilot
I don’t propagate techbro “AI” bullshit peddled by companies trying to make a quick buck
Also, in the world of science and technology a “Standard” means something. Something that’s not a link to a wikipedia page.
It’s still anthropomorphising software and it’s fucking cringe.
*bad Devs
Always look on the official repository. Not just to see if it exists, but also to make sure it isn’t a fake/malicious one
*bad Devs
Or devs who don’t give a shit. Most places have a lot of people who don’t give a shit because the company does not give a shit about them either.
What’s the diff between a bad dev and a dev that doesn’t care? Either way, whether ist lack of skill or care, a bad dev is a bad dev at the end of the day.
I can be good at a trade, but if I’m working for a shit company with shit pay and shit treatment, they’re not going to get my best work.
You get out what you put in, that’s something employers don’t realise.
Garbage in, garbage out, after all
I just want an LLM with a reasonable context window so we can actually write real working packages with it.
The demos look great, but it’s always just around 100 lines of code, which is beginner level. The only use case right now is fake packages.
I’m not particularly interested. Some on my team are playing with it, but I honestly don’t see much point since they spend more time fixing the generated code than they would writing it.
And I don’t think it’ll ever really work well (in the near-ish future) for the most common type of dev work: fixing bugs and making small changes to existing code.
It would be awesome if there was some kind of super linter instead. I spend far more time reading code than writing it, so if it can catch bugs, that would be interesting.
In my experience with Codeium, it sometimes works ok for three or four lines of code at once. I’ve actually had a few surprises where it nailed what I was going for where I didn’t expect it. But most of the time, it’s just duplicating code from elsewhere in the same file, which usually doesn’t make sense.
It’s also pretty good for stuff where I’d usually build some exotic regex to search/replace (or do it manually, because it’d take longer to come up with the expression), like transforming an enum into a switch construct for its members, or mapping said enum to a string of the member’s name.
This is very far from taking over my job, though. I’d love to be more of a conductor than the guy playing all instruments in the orchestra at once.
To each their own of course. It just seems like the productivity gains are perceptual, not actual.
For an enum to a switch, I just copy the enum values and run a regex on those copied lines. Both would take me <30s, so it’s a wash. That specific one would be trivial with most IDEs as well, just type “switch (variable) {” and it could autocomplete an exhaustive switch, all without LLMs.
Then again, I’m pretty old school. I still use vim as my editor (with language server plugins), and I’m really comfortable with those kinds of common tasks. I’m only going to bother learning to use the LLM if it’s really going to help (e.g. automate writing good unit tests).
Sometimes those things are way more complex, for example when it’s about matching over a string rather than an enum to convert it into an enum. Typing out a regex would take me maybe 10mins or more, and with the LLM I can just describe roughly what I want (since it knows the language, I don’t have to explain it in detail, just something like “make this into a switch statement” is sufficient usually).
10mins at a time really adds up over a full work day.
Claude is 200k
those are tokens not lines of code…
Yeah sorry, I thought that was clear. It’s how context is measured.
