"AI" is a failed technology, in the sense that it's neither fit for purpose, nor a likely path to its stated end goal of "AGI", but a lot of people's profits currently depend on pretending it's not.
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The problem is that you are building shit.
Even if all your arguments suddenly got bopped on the head by the blue fairy and became true you are demonstrating an ABSURD degree of moral failure by using a system designed, by the creators' OWN WORDS, to de-skill and infantilize the entire populace so they can sell their own stolen work back to them on a fucking meter.
Bud, if you can wrangle ok code out of the fascist idiot machine, you are still an absolute piece of fascist shit.
@TeflonTrout please go fuck yourself properly
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Sea Lion
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"AI" is a failed technology, in the sense that it's neither fit for purpose, nor a likely path to its stated end goal of "AGI", but a lot of people's profits currently depend on pretending it's not. I am curious to see how long the hype will last once the Nvidia ouroboros ends and money stops being pumped into marketing.
@Gargron as long as it keeps improving money will go into it -
i never said bigger is better. @Gargron brought up the size of mastodon as an argument for his authority, so i was responding in the same terms. not sure where you got the idea that i was comparing codebase sizes.
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"AI" is a failed technology, in the sense that it's neither fit for purpose, nor a likely path to its stated end goal of "AGI", but a lot of people's profits currently depend on pretending it's not. I am curious to see how long the hype will last once the Nvidia ouroboros ends and money stops being pumped into marketing.
It doesn’t seem like there’s any pathway to profitability. These guys are living in denial after epic level of Nepo baby money fire storm.
They all believe they could smother the problem in money and they would come out on top. This is how they usually operate so arguably it’s understandable why they went this way.
They are also insane
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i never said bigger is better. @Gargron brought up the size of mastodon as an argument for his authority, so i was responding in the same terms. not sure where you got the idea that i was comparing codebase sizes.
You wrote
"I use AI agents to build real software (bigger codebase than mastodon btw)"
in the post I'm replying to.
First question still outstanding.
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if you’ve never used it, then yes, you’re not in a position to judge what it looks like when used properly. being an experienced engineer and maintainer gives you plenty of expertise in software engineering, but it doesn’t magically give you first-hand experience with a tool you explicitly said you’ve never used.
you can absolutely argue that you don’t want to use it. that’s a different claim.
@skavish @Gargron I have used it "properly" and I think that's an invalid argument.
Software projects fundamentally depend on repeatable processes and human interaction.
"You're just not doing it right" is a cop-out from admitting the technology doesn't produce repeatable successes, complete ones, or even solutions that are what you asked for
If you know what you're doing, and have time to do it yourself, you don't need AI to write outstanding code.
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@Gargron It probably writes better code than you do at this point. Anyone who calls it spaghetti code TODAY has no clue what it’s capable of.
There’s a reason mathematicians are freaked out. Their heads aren’t in the sand
@j_s_j Mathematicians aren't freaked out because of how comprehensible and well-structured the LLM output is. It's the opposite. The models produce results (Lean code resulting in a "yes" or "no" to hard mathematical questions), accompanied by fever dreams of text that may or may not correspond to the Lean code. This is still apocalyptic for the field of mathematics because the "yes"es and "no"s themselves stand, regardless of the text quality and code quality. This approach to code isn't feasible if your software is to be used more than once, deal with the wildest inputs, and may end up running in a power plant.
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@negative12dollarbill why should i disclose what software i work on? i do not work on open source, and i have nothing to prove to you. if you are genuinely curious, you can always look me up. somehow i suspect you are more interested in arguing than finding out.
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@skavish @Gargron I have used it "properly" and I think that's an invalid argument.
Software projects fundamentally depend on repeatable processes and human interaction.
"You're just not doing it right" is a cop-out from admitting the technology doesn't produce repeatable successes, complete ones, or even solutions that are what you asked for
If you know what you're doing, and have time to do it yourself, you don't need AI to write outstanding code.
ai does not have to be perfect to be useful. repeatability comes from tests, reviews, and engineering discipline. you are describing a tool that needs to be managed and pretending that proves it is useless.
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@negative12dollarbill why should i disclose what software i work on? i do not work on open source, and i have nothing to prove to you. if you are genuinely curious, you can always look me up. somehow i suspect you are more interested in arguing than finding out.
Well at the time you made those statements, you clearly thought they would add to your authority on this topic.
Now it's rude to ask you to explain them. I don't really know why that changed.
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ai does not have to be perfect to be useful. repeatability comes from tests, reviews, and engineering discipline. you are describing a tool that needs to be managed and pretending that proves it is useless.
@skavish@welley.social Whose pretending? It is useless, for me.
End of statement.
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ok, look, you probably know who Linus Torvalds is, right? if not google it. then check it out: https://thenewstack.io/torvalds-linux-ai-stance/
Ah yes, invoking a notable person. My philosophies are all in shambles now!
Just wait until they shut off the tap on that juicy subsidized compute. When faced with the real costs you will not view this as efficient, and it is not efficient.
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@j_s_j Mathematicians aren't freaked out because of how comprehensible and well-structured the LLM output is. It's the opposite. The models produce results (Lean code resulting in a "yes" or "no" to hard mathematical questions), accompanied by fever dreams of text that may or may not correspond to the Lean code. This is still apocalyptic for the field of mathematics because the "yes"es and "no"s themselves stand, regardless of the text quality and code quality. This approach to code isn't feasible if your software is to be used more than once, deal with the wildest inputs, and may end up running in a power plant.
@dss You’re right about *one* reason mathematicians are freaking out. Models also had trouble drawing hands a couple of years ago. There are human authored papers that can only be vetted properly by a handful of experts in related fields. When something comes along and purports to solve something humans haven’t for nearly a century, it shouldn’t be surprising the explanation needs analysis.
Mathematicians aren’t saying models aren’t making real discoveries.
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the environmental-impact argument against AI doesn’t really hold water when you put the numbers in context. the comparison with everyday activities like eating a burger is pretty revealing.
https://welley.social/@skavish/posts/pt_01m4nt61s1ecjrvbczk5zb45z6
@skavish a few remarks:
- you choose a meat based meal, the carbon footprint of a balanced plant based meal is lower. We know eating meat every day isn't sustainable anyway, so you're not going anywhere by comparing two unsustainable things. To reduce CO2 emissions we need to reduce both of these things.
- the hardware manufacturing and the model training seem to be a big part of the footprint of AI, like the cow in your burger. We don't have reliable numbers from AI companies, but we can't consider them as negligible.
- at least the burger feeds you.. how vital is the result of those 6 hours of computation?cc @Gargron
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open-weight models are pretty capable now
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open-weight models are pretty capable now
@skavish Uh huh
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@skavish a few remarks:
- you choose a meat based meal, the carbon footprint of a balanced plant based meal is lower. We know eating meat every day isn't sustainable anyway, so you're not going anywhere by comparing two unsustainable things. To reduce CO2 emissions we need to reduce both of these things.
- the hardware manufacturing and the model training seem to be a big part of the footprint of AI, like the cow in your burger. We don't have reliable numbers from AI companies, but we can't consider them as negligible.
- at least the burger feeds you.. how vital is the result of those 6 hours of computation?cc @Gargron
@eve my point is that ai's environmental impact is constantly presented as some enormous problem, while in reality, even 170 hours of agent use can have a smaller footprint than eating a burger. and that is before we even compare it with things like driving an suv, flying, air conditioning, or heating a house. somehow, those rarely get the same level of outrage. perspective matters.
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@crazyeddie you are missing the point. his engineering expertise isn't in question. he explicitly said he's never used AI. so how can he confidently judge what AI-generated code looks like when the tools are used effectively?
@skavish Yeah, I tore that point apart. Maybe you missed it.
