311–320 of 322 posts
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Its a question designed to fool the AI. It's like saying that a person doesn't understand the limitations of reality when they fall for a magic trick.
These aren't the same thing. You can't fool an AI because it isn't using its own judgement.
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Its a question designed to fool the AI. It's like saying that a person doesn't understand the limitations of reality when they fall for a magic trick.
These aren't the same thing. You can't fool an AI because it isn't using its own judgement.
Earlier quoted context omitted.
These aren't the same thing. You can't fool an AI because it isn't using its own judgement.
You can fool an AI as evidenced by them being fooled. They demonstrably appear to be working through a problem and get fooled by the wording of the problem. If you think differently, merely asserting it is not the way to convince people that what they see is wrong.
An LLM is (effectively) just a really, really elaborate "choose your own adventure" book.
It's not "working through" problems, it's just tracing a route through an pre-defined information space. It's not actually thinking, it just does a good impression of it.
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I think that the problem basically arises due to the fact that the technology is recent and the opinions on it are hard to make and even if we do end up making opinions, then my opinion is of the fact that I am more than happy for AI to suddenly vanish but clearly that can't be the case and there have been some long term discussions that I can point out to. We can however change our opinions on AI and the culture sur…
Thanks for the detailed answer, which pretty contrasts with harsh brevity of my comment (sorry if it offended you), I wish you well too of course, me myself being a half-techie/half-artist torn about this double-edgedness of things, I know why there's that split, we all adore the figurative hammer that helps driving nails into walls, but hate it when someone starts using it to drive nails into their or their neighbor…
This analogy is quite beautiful.
> The results were not long in coming, I already hear their complaints about getting lost in the codebase they themselves created, and getting dumber.
I think that there are some ways that people are trying to create an AI-use policy, here is one that I found on hackernews which I found interesting: https://libls.org/ai-use
Basically, I think that if its a personal thing then sure all bets are off and you can use vibe-coding or whatever on personal projects or prototypes
BUT, you can't really let AI do your job and somehow justify it and its costs (both in terms of tokens and the cost of tearing down the codebase with slop) and there should be a strict code of conduct regarding AI-use.
I feel like we are going to see more attempts at trying to solidify a procedure regarding AI-use and for me, the libls.org/ai-use makes somewhat sense and I'd be curious to think about your opinion.
That being said, it might not still be used within the structures of large companies because of the C-suite/investors issues that I mentioned but I am hopeful that eventually the mania regarding completely unfiltered AI-use slows down.
Like many crafts (painting, music, etc) the true test of great software is time. Not because of taste, but because software is a living artefact that must evolve.
Only over time does a human developer realise they have "painted themselves into a corner" and chosen the wrong abstractions. And it will be the same with vibe coding (i.e. where code is not architected and reviewed exhaustively by a human).
Because companies won't surface their internal codebases, the most likely signs of such problems with be the reliability of applications and services. I don't know if recent outages are indicative of changes in code practice, or just coincidence, but we'll find out over time.
Agents aren't yet strong general reasoners - they are good at reasoning in the shape of their training corpus - so it's essential that important code is reviewed by human experts.
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You can fool an AI as evidenced by them being fooled. They demonstrably appear to be working through a problem and get fooled by the wording of the problem. If you think differently, merely asserting it is not the way to convince people that what they see is wrong.
You can't fool an inanimate object. An LLM is (effectively) just a really, really elaborate "choose your own adventure" book. It's not "working through" problems, it's just tracing a route through an pre-defined information space. It's not actually thinking, it just does a good impression of it.
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You can fool an AI as evidenced by them being fooled. They demonstrably appear to be working through a problem and get fooled by the wording of the problem. If you think differently, merely asserting it is not the way to convince people that what they see is wrong.
You can't fool an inanimate object. An LLM is (effectively) just a really, really elaborate "choose your own adventure" book. It's not "working through" problems, it's just tracing a route through an pre-defined information space. It's not actually thinking, it just does a good impression of it.
You can't constrain foolability to just the animate objects.
Foolability is based on intelligent processing.
To what degree such an intelligence needs to be developed is not defined at all (we can, for example, trivially fool a doog using one of many tricks, and a dog is hardly general intelligence).
Thus far, the inteligent processing we knew concerned animate objects. But we now have developed software/hw combos that exhibit intelligent processing. Is it enough to actually be intelligent or to be fooled?
We don't know. We do know it's enough to appear intelligence, convince people that it is intelligent, and to appear to be fooled.
But even if we think of LLM AI as mere mechanistic process with no emergent intelligence, who said one can not fool a mechanistic process? We can fool even simple pre-LLM gaming AI systems (based on simplistic heuristics) just fine.
I still cannot wrap my head around people who spawn tens and sometimes thousands of agents hoping for the best and then saying how little token limits are. The only way that is possible is when your work is superficial and you have no idea what you are doing (or it’s a hobby project).
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You can't fool an inanimate object. An LLM is (effectively) just a really, really elaborate "choose your own adventure" book. It's not "working through" problems, it's just tracing a route through an pre-defined information space. It's not actually thinking, it just does a good impression of it.
> You can't fool an inanimate object You can't constrain foolability to just the animate objects. Foolability is based on intelligent processing. To what degree such an intelligence needs to be developed is not defined at all (we can, for example, trivially fool a doog using one of many tricks, and a dog is hardly general intelligence). Thus far, the inteligent processing we knew concerned animate objects. But we now…
'Fooling' something, essentially to deceive or trick, is defined as causing someone to believe an untruth. LLMs don't hold beliefs (neither do mechanistic processes), and they aren't a someone.
You can widen out the definition of the word but that generally makes language weaker - interestingly, semantic drift is a big issue for LLM's.
We have different opinions, and that's fine. Have a good day.
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I never understood this perspective. Just because a person's behavior is market-rational, it does not mean they can't be criticized for externalities. That is, in fact, an important thing to do. It turns those externalities into public perception, which turns into market forces that adjust the behavior, if you want to think purely in market terms. The analogy with Budweiser is not a good one. This would be the CEO of…
Of course they can be criticized, we can criticize the ExxonMobil CEO the same way and get nowhere The point is, blaming them is pointless, if it wasn't them it would be someone else. How do we react?