"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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@Gargron
I totally agree. What I also dislike is renaming things with "AI" just to make it sound advanced.I heard an advert today for British Telecom saying their "AI business tool" could help your small business. That "tool" was booking tables (that's a CMS/database, not AI) and answering calls (that's an answering machine (at a push, IVR), not AI) etc.
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@Gargron counterpoint: we are well past the point of no return for agentic engineering. There will always be purists who insist on writing code by hand but we aren’t returning to that being the default even after the bubble pops. And I think quiet use of AI as glue will propagate more or less unseen through a lot of tech until it is the expected/desired thing vs a bolted-on buzzword.
Are there myriad problems with both of these? Of course. But that much is not “failure” in any meaningful sense.
@mellowfish @Gargron "agentic" engineering is only effective if you place no weight on the risks of mistakes
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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 and oracle wishes it hadn't burnt all it's cash last october...
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@Gargron jepp we will see what is going to happen with this AI stuff. Everyone IT related knows what is going to be happening.
The entire world knows it. As we say in Germany "lasse komme".
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@Gargron counterpoint: we are well past the point of no return for agentic engineering. There will always be purists who insist on writing code by hand but we aren’t returning to that being the default even after the bubble pops. And I think quiet use of AI as glue will propagate more or less unseen through a lot of tech until it is the expected/desired thing vs a bolted-on buzzword.
Are there myriad problems with both of these? Of course. But that much is not “failure” in any meaningful sense.
Let's see when subsidize usage stops and tokens start costing 10x.
Also, if your prediction is right, then software is doomed.
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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
(just leaving this here as support and contrast to the AI bros losing their sht ^^") -
@clayote you are confusing two arguments. I am not claiming Gargron would get good results, I am saying you cant know what results you'd get without actually using the tools. I use them daily to build real software, so I have firsthand experience. you keep demanding evidence while dismissing the possibility of evidence you haven't personally examined. the irony is hard to miss.
This argument makes no sense.
You don't have to try something to judge it, in fact personal experience is anecdotical and not a good foundation for judgment.
Knowing what the tool is and how it works is more valuable as a judgment criteria.
Especially with something like LLM that "seem" absolutely fantastic at first touch.You're looking like a predicant saying "when you're blessed by the faith, you'll believe!"
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This argument makes no sense.
You don't have to try something to judge it, in fact personal experience is anecdotical and not a good foundation for judgment.
Knowing what the tool is and how it works is more valuable as a judgment criteria.
Especially with something like LLM that "seem" absolutely fantastic at first touch.You're looking like a predicant saying "when you're blessed by the faith, you'll believe!"
Besides that, your tool is built on stolen material, near-slavery training work, it's an ecological disaster and has been designed to reduce the bargain power of intellectual worker like yourself.
You have to be completely ignorant or a complete asshole to be ok with all this.
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Not relevant to whether or not it has failed or works poorly, which is what the original post was about
It is, you can't judge the success and viability of something without considering real cost and externalities.
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@rainynight65 @skavish @Gargron The thing is, for 90% of software, "don't care" probably is the correct approach from a business management PoV.
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It is, you can't judge the success and viability of something without considering real cost and externalities.
That much is true. What do you think of local models?
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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 I basically use it just as a glorified stackoverflow/google. Am I using it wrong?
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@Gargron What we term AI today is misnamed and misused and oversold.
But the technology as such (i.e. LLMs and Neural Networks and the like) isn't useless.
E.g. my daughter is training AI to recognize and classify life in ROV videos from the deep sea ocean floors.
Many such applications. "AI" doesn't get bored and is extremely good at spotting patterns and things that break the patterns.
But, yeah, it is shit for coding...
@steinarb The thing is, you obviously know the difference between those models, yet you still managed to somehow confuse them. LLMs have clearly nothing to do with what your daughter does. AI is a buzzword and it basically means nothing at this point. There are lots of specialized ML (machine learning) models that are actually helpful (like what your daughter does). But LLMs ain't it, chief. They're just a waste of electricity and water.
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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 It is so refreshing to see one of your favourite devs speak in this way about this sh*t. I swear, AI is really bringing my mood down as of late.
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That much is true. What do you think of local models?
@golemwire Local model of what? Language model for general purpose/coding?
They are better under the consume aspect, but they share the same problem in all the other aspects (stolen training data, salevry-like training, sociological and psychological impact and so on). -
"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 I disagree with calling it a failed technology. The Google Brain project that spun up the topology that made the LLMs in 2016 functional was a huge step forward in machine learning in general. We've been working on AI for 70 years. No matter what they want to call it, it's more than a fucking chatbot. We need to progress this. We just need to stop treating it like it's something it isn't.
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@clayote the difference is that i actually use the tools and build real software with them. you are arguing about a guitar you have never played, based on people you do not respect playing it badly. that is not exactly a solid basis for judging the instrument.
@skavish @clayote Great, if you are looking for someone who has actually used thesr tools in real life, I'll raise my hand. I was lead of DevAI tools at a major tech company, and I've used them to build websites, infra, and other tooling.
While you can get these tools to write code that "works", in my experience they constantly add tech debt to your project, sometimes in obvious ways, often in subtle ways. Since they have no mental model of how the code base should work, they are constantly violating API conventions. They tend towards verbosity -- in one project, it implemented Haversine distance repeatedly in whatever class it felt it needed it, despite explicit instructions in .md files to use the canonical version.
You can of course keep correcting the bot and eventually get decent results. But that assumes that you are doing thorough code review of *everything*, and what's more, that you yourself actually understand a code base that you aren't actively engaged in writing. That's *hard*.
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@skavish @clayote Great, if you are looking for someone who has actually used thesr tools in real life, I'll raise my hand. I was lead of DevAI tools at a major tech company, and I've used them to build websites, infra, and other tooling.
While you can get these tools to write code that "works", in my experience they constantly add tech debt to your project, sometimes in obvious ways, often in subtle ways. Since they have no mental model of how the code base should work, they are constantly violating API conventions. They tend towards verbosity -- in one project, it implemented Haversine distance repeatedly in whatever class it felt it needed it, despite explicit instructions in .md files to use the canonical version.
You can of course keep correcting the bot and eventually get decent results. But that assumes that you are doing thorough code review of *everything*, and what's more, that you yourself actually understand a code base that you aren't actively engaged in writing. That's *hard*.
@skavish @clayote Yes, humans write shitty code too. That's why the study of software engineering processes and culture have been so critical to our field. We've learned over time how to create a process that generated useful code with imperfect humans.
But the lessons we think we learned with human software engineering are being forgotten, or what's worse, misinterpreted. They were designed for humans, who work by building internal mental models of the world, and instinctually strive to sync their mental models with their colleagues. But LLMs do not build mental models. They predict what is most likely based on their context window. That's a vast and critical difference.
As these tools are being used today, they are becoming engines of tech debt creation. And anyone who's worked in software knows what a trap that can be. The gains become incrementally smaller as the inertia of tech debt becomes larger. At some point, nobody knows how it works any more, and then you're fucked.
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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 The pursue of strong AI or the so-called “AGI” is disgusting and undesirable to start with.
So, even if it was a path to “AGI” I would fucking hate and try to boycott it.
