"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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@golemwire @Nead There are plenty of times when it fails miserably too.
Maybe on this problem it works, with an expensive model, and with the help of another piece of software that does all the heavy lifting. All it must do is what computers do best, repetitive work, in this case, backtracing spaghetti code, where it can clearly validate its success.
But for many programming projects, success and failure do not have this self-proving nature handed to them on a silver platter
I agree. AI is way overused and overhyped. I'm arguing for it not being a failure. It has many places it fails.
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@Gargron @imhotep @skavish On the other hand you say in another post, that you have never used AI, but maintaining one of the biggest FOSS project on GitHub is enough expertise.
Im no Dev, but I assume Linux may be a even bigger FOSS project and Linus explored AI. According to your argumentation, he is as capable as you, if not more, to make guesses about GenAI.
Or what’s the difference, that make your opinion superior to his one?
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@Gargron @imhotep @skavish On the other hand you say in another post, that you have never used AI, but maintaining one of the biggest FOSS project on GitHub is enough expertise.
Im no Dev, but I assume Linux may be a even bigger FOSS project and Linus explored AI. According to your argumentation, he is as capable as you, if not more, to make guesses about GenAI.
Or what’s the difference, that make your opinion superior to his one?
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@Gargron @mellowfish Eugen, you worded that far more diplomatically than I could have managed. I had to delete my reply.
@zalasur @Gargron @mellowfish Agreed!
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@golemwire @Gargron
LLMs are also a failure in that they give completely authoritative sounding output that is often wrong, and it can take as much work to determine whether they are correct as to produce the desired results without LLM.I do believe that AIs are failure when it comes to generic question-answering, like how one's parents probably use ChatGPT right now.... But my interactions with LLMs are usually with the LLM in a harness, with the LLM operating it. That they're not a failure at.
E.g. Kagi Assistant -- I'll give a long rambling question like "There's an article online where the director, a writer, or something, for Cloudy with a Chance of Meatballs says something about Flint needing more compute (I'm sure it was phrased differently). Where's that article?" That was my last query, I had tried searching the web normally but to no avail. The LLM generated a plan and then used Kagi's harness to perform web searches based on the plan to find what I wanted. https://assistant.kagi.com/share/8fa7d889-f4a5-4b31-8898-8ab8cc13658e (I'm realizing that the LLM basically mocked vibecoders at the end of that thread, LOL, kinda deserved)
My point is that they are pretty much failures at raw question-answer, due to hallucinations, but are great with most of the other tasks you'd use a harness with.
If they're supposed to be everything marketers want them to be, they're definitely a failure. Many vibecoders ignore quality. I pretty much just ignore them and find something actually useful to me.
CC: @Gargron@mastodon.social
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@Gargron just popping in to say thanks for this post, it's been very useful for #WhackATroll
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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 interesting times. Will the bubble burst? I guess we'll have to wait and see.
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@skavish I find takes like this increasingly hilarious. There’s the magical mythical engineers “doing it right” while the vast majority of users - by my own observation - are pumping out absolute trash. The incentive for quality just does not exist. Some people can build quality systems in spite of that but it is not the norm.
@dandean @skavish these two posts sums it up for me, you both get a star
For what is wurth: @skavish your point is being pulled out of context a couple of times and that is a shame. You are genuielly trying to provide a perspective/insight.
And you’re wright: ‘only if you open-mindly try it.. ‘
@dandean thx for the clearity
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@Gargron
I am fascinated by your ad hominem attack, but I'm not here to score points or win a right-or-wrong debate.Why not address the substance of my response and engage in a fair debate based on facts and experiences?
Let me start:
What if a technology doesn't need to provide 100% reliable information to be useful, provided its limitations are understood and appropriately managed?And what if future developments improve the reliability of these models and address some of their current limitations? Would AI still be inherently dangerous and irresponsible as a technological tool?
I'm genuinely interested in the reasoning behind your conclusion that AI is a failed technology.
@Luminous_J
"If it was something else, would it still be the same?"We can talk about that when it is that something else. For now, and for any moment in the present, it is what it is.
@Gargron -
"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 business case for building a superhuman AI never really stood up: https://findthethread.blog/Artificial-Investment/
On the other hand once the worst of the hype fades, there is value there that can be salvaged. We saw this cycle play out with drones, 3D printing, and even (Cthulhu help us all) blockchains. -
@clayote LLM output depends heavily on who is using it. a bad engineer will produce bad code with an LLM, just faster. a great engineer can use it to produce great code, faster.
@Gargron may have reviewed plenty of LLM-generated code. that doesn't mean he has seen what these tools can do in the hands of someone who knows how to use them. that is precisely my point: if you have never used the tools yourself, you are judging them from the outside, without understanding what you're missing.
While it is possible for a good engineer to produce good code with an LLM, it requires a significant amount of back and forth, a lot of patience, and ends up not saving as much time. Much of the savings is eaten up in the careful review and iteration on the solution. It is not clear that you actually save money doing this.
On the flip side. Generating spaghetti code that works is way faster. So when people are operating on a deadline, what do they do? They generate spaghetti code and shop for reviewers who will stamp it.
The biggest difference post LLM? The speed of spaghetti generation.
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@dandean @skavish these two posts sums it up for me, you both get a star
For what is wurth: @skavish your point is being pulled out of context a couple of times and that is a shame. You are genuielly trying to provide a perspective/insight.
And you’re wright: ‘only if you open-mindly try it.. ‘
@dandean thx for the clearity
@theatredesvarietes @skavish to clarify, my critique is on the point @skavish is trying to make. We are stuck living in the real world. In the real world, the incentives produced by LLMs encourage bad outcomes. It’s possible to work in spite of those incentives at the individual level, but the broader reality is the nature of the system, and that reality is a firehose of slop.
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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
here's a little something to hopefully help it end sooner:
https://thoughtlost.org/nosingularity/ -
@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 rapist take
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@mirabilos @mellowfish Like moths to a flame. Happy to be of service.
@Gargron @mirabilos @mellowfish or flies to a turd 🪰
edit: I am talking about AI-bros drawn to defending LLM usage, no shade intended or implied on you Eugen
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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.
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@Gargron @imhotep @skavish On the other hand you say in another post, that you have never used AI, but maintaining one of the biggest FOSS project on GitHub is enough expertise.
Im no Dev, but I assume Linux may be a even bigger FOSS project and Linus explored AI. According to your argumentation, he is as capable as you, if not more, to make guesses about GenAI.
Or what’s the difference, that make your opinion superior to his one?
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Sea Lion
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@Gargron this got boosted into my timeline.
You are conflating some llms with the umbrella of ai technologies in an apparent reaction to how those companies train and market their llms.
The problem isn't the technology. It's people who are lumped up in trenchcoats of corporations.
Be critical, but be accurate. You're half there.
@knowprose "not all men"-ass take
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@oldguycrusty @Gargron you think the extra half trillion a year for the pentagon is intended for humans?
I take your point.
But still, I understand the industry investment to be on the order of $2.5 trillion in data center infrastructure alone.
As huge a taxpayer handout as that may be, it still doesn't even come close to covering cost, much less get the industry to profitability.
So what is the revenue model? What's the plan?
I don't get it.
