Oftentimes, plausible code is good enough, hence why people keep using AI to generate code. This is a distinction without a difference.
LLMs work best when the user defines their acceptance criteria first
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Re: LLMs work best when the user defines their acceptance criteria first
#262Ok, I’ll bite: how is that different from humans?
Human behaviour is goal-directed because humans have executive function. When you turn off executive function by going to sleep, your brain will spit out dreams. Dream logic is famous for being plausible but unhinged. I have the feeling that LLMs are effectively running on dream logic, and everything we've done to make them reason properly is insufficient to bring them up to human level.
Some of my best code comes from my dreams though.
Re: LLMs work best when the user defines their acceptance criteria first
#263Ok, I’ll bite: how is that different from humans?
Human behaviour is goal-directed because humans have executive function. When you turn off executive function by going to sleep, your brain will spit out dreams. Dream logic is famous for being plausible but unhinged. I have the feeling that LLMs are effectively running on dream logic, and everything we've done to make them reason properly is insufficient to bring them up to human level.
A prompt for an LLM is also a goal direction and it'll produce code towards that goal. In the end, it's the human directing it, and the AI is a tool whose code needs review, same as it always has been.
Re: LLMs work best when the user defines their acceptance criteria first
#264Earlier quoted context omitted.
"Even if that were true, it is not true that when you ask those people to do otherwise they simply pretend to have done it and forget you asked later." I admire your experience with people.
The point is, that's not the typical experience and people like that can be replaced. We don't willingly bring people like that on our teams, and we certainly don't aim to replace entire teams with clones of this terrible coworker prototype.
Not only have i never had a coworker as bad as these people describe, the point is as you say: why would I want an LLM that works like these people's shitty coworkers?
My worst coworkers right now are the ones using Claude to write every word of code and don't test it. These are people who never produced such bad code on their own.
So the LLMs aren't just as bad as the bad coworkers, they're turning good coworkers into bad ones!
Re: LLMs work best when the user defines their acceptance criteria first
#265Ok, I’ll bite: how is that different from humans?
Human behaviour is goal-directed because humans have executive function. When you turn off executive function by going to sleep, your brain will spit out dreams. Dream logic is famous for being plausible but unhinged. I have the feeling that LLMs are effectively running on dream logic, and everything we've done to make them reason properly is insufficient to bring them up to human level.
And yet LLM’s are incredibly useful as they are right now.
Re: LLMs work best when the user defines their acceptance criteria first
#266Ok, I’ll bite: how is that different from humans?
It's much easier to fire an employee which produces low quality/effort work than to convince leadership to fire Claude.
Re: LLMs work best when the user defines their acceptance criteria first
#267This is my experience with how LLMs "draft" legal arguments: at first glance, it's plausible — but may be, and often is, invalid, unsound, and/or ill-advised. The catch is that many judges lack the time, energy, or willingness to not only read the documents in detail, but also roll up their sleeves and dig into the arguments and cited authorities. (Some lack the skills, but those are extreme cases.) So the plausible…
>" justice suffers"
Possible. It also suffers when majority simply can not afford proper representation
Re: LLMs work best when the user defines their acceptance criteria first
#268Ok, I’ll bite: how is that different from humans?
Human behaviour is goal-directed because humans have executive function. When you turn off executive function by going to sleep, your brain will spit out dreams. Dream logic is famous for being plausible but unhinged. I have the feeling that LLMs are effectively running on dream logic, and everything we've done to make them reason properly is insufficient to bring them up to human level.
LLMs are literally goal machines. It’s all they do. So it’s important that you input specific goals for them to work towards. It’s also why logically you want to break the problem into many small problems with concrete goals.
Re: LLMs work best when the user defines their acceptance criteria first
#269This is my experience with how LLMs "draft" legal arguments: at first glance, it's plausible — but may be, and often is, invalid, unsound, and/or ill-advised. The catch is that many judges lack the time, energy, or willingness to not only read the documents in detail, but also roll up their sleeves and dig into the arguments and cited authorities. (Some lack the skills, but those are extreme cases.) So the plausible…
> This is my experience with how LLMs "draft" legal arguments: at first glance, it's plausible — but may be, and often is, invalid, unsound, and/or ill-advised.
Correct, and this of course extends past just laws, into the whole scope of rules and regulations described in human languages. It will by its nature imply things that aren't explicitly stated nor can be derived with certainty, just because they're very plausible. And those implications can be wrong.
Now I've had decent success with having LLMs then review these LLM-generated texts to flag such occurences where things aren't directly supported by the source material. But human review is still necessary.
The cases I've been dealing with are also based on relatively small sets of regulations compared the scope of the law involved with many legal cases. So I imagine that in the domain you're working on, much more needs flagging.
Re: LLMs work best when the user defines their acceptance criteria first
#270Earlier quoted context omitted.
It’s not. LLMs are just averaging their internet snapshot, after all. But people want an AI that is objective and right. HN is where people who know the distinction hang out, but it’s not what the layperson things they are getting when they use this miraculous super hyped tool that everybody is raving about?
By now, a few years after ChatGPT released, I don't think anyone is thinking AI is objective and right, all users have seen at least one instance of hallucination and simply being wrong.
Sorry I can think of so many counter examples. I also detect a lot of “well it hallucinates about subject X (that the person knows well, so can spot the hallucination)” but continue to trust it on subjects Y and Z (which the person knows less well so can’t spot the hallucinations).
YMMV.