To be honest the impression I've gotten is that some people are just very interested in talking about not anthropomorphizing AI, and less interested in talking about AI behaviors, so they see conversations about the latter as a chance to talk about the former.
Outside the technical world it gets much worse. There are people who killed themselves because of LLMs, people who are in love with them, people who genuinely believe they have “awakened” their own private ChatGPT instance into AGI and are eschewing the real humans in their lives.
It's going to take a lot to get him out of that mindset and frankly I'm dreading trying to compare and contrast imperfect human behaviour and friendships with a sycophantic AI.
I suppose this war will be fought until people are out of energy, and if reason has no place, it is reasonable to let others tire themselves out reiterating statements that are not designed to bring anyone closer to the truth.
E.g. when I first started learning webdev, I didn’t think about ‘servers’. I just knew that if I uploaded my HTML/PHP files to my shared web host, then they appeared online.
It was only much later that I realized that shared webhosting is ‘just’ an abstraction over Linux/Apache (after all, I first had to learn about those topics).
I asked Claude to write a E-AC3 audio component so I can play videos with E-AC3 audio in the old version of QuickTime I really like using. Claude's decoder includes the ability to write debug output to a log file, so Claude is studying how QuickTime and the component interact, and it's controlling QuickTime via Applescript.
Sometimes QuickTime crashes, because this ancient API has its roots in the classic Mac OS days and is not exactly good. Claude reads the crash logs on its own—it knows where they are—and continues on its way. I'm just sitting back and trying to do other things while Claude works, although it's a little distracting that something else is using my computer at the same time.
I really don't want to anthropomorphize these programs, but it's just so hard when it's acting so much like a person...
I’m sure you knew that your code was running on computers somewhere even when you first started and wasn’t running in a literal “cloud”.
It’s about as tiring as people on HN who know just a little about LLMs thinking they are sounding smart when they say they are just advanced autocomplete. Both responses are just as unproductive
Meh, I just knew that the browser would display HTML if I wrote it, and that uploading the HTML files made them available on my domain. I didn’t really think about where the files went, specifically.
Try asking an average high school kid how cloud storage works. I doubt you’ll get any further than ‘I make files on my Google Docs and then they are saved there’. This is one step short of ‘well, the files must be on some system in some data center’.
I really disagree that “people who come on HN and say “there is no such thing as serverless and there are servers somewhere” think they are sounding smart when they are adding nothing to the conversation.” On the contrary, it’s an invitation to beginning coders to think about what the ‘serverless’ abstraction actually means.
I would call "fuck around and find out" a rather simple approach. It is why we use it! It is why lots of animals use it. Even very dumb animals use it. Though, we do notice more intelligent animals use more efficient optimization methods. All of this is technically hypothesis testing. Even a naive grid search. But that is still in the class of "fuck around and find out" or "brute force", right?
I should also mention two important things.
1) as a human we are biased to anthropomorphize. We see faces in clouds. We tell stories of mighty beings controlling the world in an effort to explain why things happen. This is anthropomorphization of the universe itself!
2) We design LLMs (and many other large ML systems) to optimize towards human preference. This reinforces an anthropomorphized interpretation.
The reason for doing this (2) is based on a naive assumption[0]: If it looks like a duck, swims like a duck, and quacks like a duck, then it *probably* is a duck. But the duck test doesn't rule out a highly sophisticated animatronic. It's a good rule of thumb, but wouldn't it also be incredibly naive to assume that it *is* a duck? Isn't the duck test itself entirely dependent on our own personal familiarity with ducks? I think this is important to remember and can help combat our own propensity for creating biases.
[0] It is not a bad strategy to build in that direction. When faced with many possible ways to go, this is a very reasonable approach. The naive part is if you assume that it will take you all the way to making a duck. It is also a perilous approach because you are explicitly making it harder for you to evaluate. It is, in the fullest sense of the phrase, "metric hacking."
The therapist thing might be correct, though. You can send a well-adjusted person to three renowned therapists and get three different reasons for why they need to continue sessions.
No therapist ever says "Congratulations, you're perfectly normal. Now go away and come back when you have a real problem." Statistically it is vanishingly unlikely that every person who ever visited a therapist is in need of a second (more more) visit.
The main problem with therapy is a lack of objectivity[1]. When people talk about what their sessions resulted in, it's always "My problem is that I'm too perfect". I've known actual bullies whose therapist apparently told them that they are too submissive and need to be more assertive.
The secondary problem is that all diagnosis is based on self-reported metrics of the subject. All improvement is equally based on self-reported metrics. This is no different from prayer.
You don't have a medical practice there; you've got an Imam and a sophisticated but still medically-insured way to plead with thunderstorms[2]. I fail to see how an LLM (or even the Rogerian a-x doctor in Emacs) will do worse on average.
After all, if you're at a therapist and you're doing most of the talking, how would an LLM perform worse than the therapist?
----------------
[1] If I'm at a therapist, and they're asking me to do most of the talking, I would damn well feel that I am not getting my moneys worth. I'd be there primarily to learn (and practice a little) whatever tools they can teach me to handle my $PROBLEM. I don't want someone to vent at, I want to learn coping mechanisms and mitigation strategies.
[2] This is not an obscure reference.
We always are speaking to our audience, right? This is also what makes more general/open discussions difficult (e.g. talking on Twitter/Facebook/etc). That there are many ways to interpret anything depending on prior knowledge, cultural biases, etc. But I think it is fair that on HN we can make an assumption that people here are tech savvy and knowledgeable. We'll definitely overstep and understep at times, but shouldn't we also cultivate a culture where it is okay to ask and okay to apologize for making too much of an assumption?
I mean at the end of the day we got to make some assumptions, right? If we assume zero operating knowledge then comments are going to get pretty massive and frankly, not be good at communicating with a niche even if better at communicating with a general audience. But should HN be a place for general people? I think no. I think it should be a place for people interested in computers and programming.
Yes this is still mechanical in a sense, but then I'm not sure what behavior you wouldn't classify as mechanical. It's "responding" to stimuli in logical ways.
But I also don't quite know where I'm going with this. I don't think LLMs are sentient or something, I know they're just math. But it's spooky.
> It wasn't a simple brute force.
"Simple" is the key word here, right? You agree that it is still under the broad class of "brute force"?
I'm not saying Claude is naively brute forcing. In fact, with lack of interpretibility of these machines it is difficult to say what kind of optimization it is doing and how complex that it (this was a key part tbh).
My point was to help with this
> I really don't want to anthropomorphize these programs, but it's just so hard when it's acting so much like a person...
> It's "responding" to stimuli in logical ways.
But the real question here, which you have to ask yourself (constantly) is "how do I differentiate a complex program that I don't understand from a conscious entity?" I guarantee you that you don't have the answer (because no one does). But isn't that a really good reason to be careful about anthropomorphizing it?
That's the duck test.
How do you determine if it is a real duck or a highly sophisticated animatronic?
If you anthropomorphize, you rule out the possibility that it is a highly sophisticated animatronic and you *MUST* make the assumption that you are not only an expert, but a perfect, duck detector. But simultaneously we cannot rule out that it is a duck, right? Because, we aren't a perfect duck detector *AND* we aren't an expert in highly sophisticated animatronics (especially of the duck kind).
Remember, there are not two answers to every True-False question, there are three. Every True-False question either has an answer of "True", "False", or "Indeterminate". So don't naively assume it is binary. We all know the Halting Problem, right? (also see my namesake or quantum physics if you want to see such things pop up outside computing)
Though I agree, it can be very spooky. But that only increases the importance of trying to develop mental models that help us more objectively evaluate things. And that requires "indeterminate" be a possibility. This is probably the best place to start to combat the cognitive dissonance.
If that's how it's phrased, and it's in a spot where that's on-topic, then obviously nobody would mind.
This subthread is talking about cases where there's a technical conversation going on and somebody derails it to argue about terminology.
I am a fan of the « Beat Your Genes » podcast, and while some of the prescriptions can be a bit heavy handed, most feel intuitively right. It’s approaching human problems as intelligent mammal problems, as opposed to something in a category of its own.
I’m highly skeptical this will happen with llms though, their output is superficially convincing but without depth and creativity.
But the question is what is special about the human machine? What is special about the animal machine? These are different from all the machines we have built. Is it complexity? Is it indeterministic? Is it more? Certainly these machines have feelings, and we need to account for them when interacting with them.
Though we're getting well off topic from determining if a duck is a duck or is a machine (you know what I mean by this word and that I don't mean a normal duck)
I’d like to think that this forum is also a place for the proverbial high school kid, who’s just learned JavaScript and deployed their first site to Vercel using their school Chromebook, to learn a thing or two from the greybeards.
Joking aside, I read too quickly. I got my wires crossed when I responded, mixing up who was who. My bad >.<
But I do agree with scarface and disagree with you. Let me try to respond to this directly. There's a lot to unpack here, but I do ask that you actually read the whole thing. There is nuance here and I think it is important.
> I’d like to think that this forum is also a place for the proverbial high school kid ... to learn a thing or two from the greybeards.
But I still do not believe that means we need to assume non-expertise.
Think of HN as a place that "greybeards" (or more accurately, experts. Because only few have gray beards) hang out, but there is no gatekeeping. We don't check your credentials when you come in nor do we ask you to pass any tests of skill. It's open to all. But this is still the place "experts" hang out. Because we don't check for credentials, we'll treat noobs as peers. Why are you saying this is bad?
Anyone is welcome to sit at the "adult table", but that means having adult conversations. Right? It'd be pretty... childish... for a child to sit at the adult table and expect everyone to start talking about kid stuff.
It's okay if newbies come in and don't understand what is being discussed. In fact, being confused is the very first step to learning! I'll put it this way: the first year (maybe 2) of my PhD I was just reading papers and had no idea what was going on. I had to work and work to understand. Had to ask lots of questions to lots of people (consequently getting over the fear of feeling dumb as well as the fear of asking questions). Then, at some point in time I realized I do know what's going on and being discussed. This is a critical skill to becoming a graybeard. You'll constantly have to wade through waters where you're in well over your head.
It is learning through immersion.
We should help noobs. I frequently say "you can't have wizards without noobs." I don't want to gatekeep and I do actually think we should help the noobs. I need this to be clear[1]
BUT that doesn't mean we should change our conversations between ourselves. To do so would destroy the very reason we come here. There are so few places on the internet where you can talk and operate under the assumption that the other person is reasonable well informed about tech. Frankly, many of those places get destroyed because they get dominated by noobs who change the average level of conversation. While we don't want to kick out noobs, it is *THEIR PREROGATIVE* to ask for help and ask for people to elaborate. There's no shame in this. It's the exact same thing we expect from another expert! It is treating noobs equally. And frankly, if people do make fun of the noobs or treat them disrespectfully I'll gladly downvote, flag them, and likely chastise them. Such a response is rather common around here too (which is what makes it welcoming to noobs).
Ultimately, unless we start credential checking (aka gatekeeping) we have 2 options:
- Treat everyone as experts
- Treat everyone as noobs
I don't come to HN to teach. Nor do I want to come here to be lectured. I would find it insulting if the presumption was that I was a noob.
I come to talk with my peers. Some are direct peers, with expertise in my domain, and some are not. I happily ask questions to those with expertise in other domains and so should noobs. But unless someone makes a pretty egregious assumption (e.g. a very niche subject), then pretty much nobody is going to say something about it. That's perfectly okay. Frankly, being comfortable with not knowing and asking for someone to elaborate is one of the, if not *THE*, most important skill required to become a graybeard. You can't know everything, even about a highly specific domain. There's infinite depth and infinite breadth.
So if you don't know, just ask. It's okay. That's really the only way we can both have expert communities AND not gatekeep.
So I ask you:
Where can g̶r̶a̶y̶b̶e̶a̶r̶d̶s̶ experts go to hang out? Specifically, to hang out with other experts.
TLDR:
If you walk into a biker bar, don't chastise someone who assumes you know something about motorcycles.
[0] >>44492437
[1] I even taught a lot during my PhD and was a rather popular TA. The reason being that I am more than happy to help and even would extend my office hours to make sure students got their questions answered. A class is formed through a partnership, not a dictatorship.
Even with the everyday machines and programs we have, we can make it behave based on random input taken for example from physical noise. It doesn't suddenly make it a special or different type of machine.
But that's not what my comment was about.
My comment was about *what the average person interprets*.
You asked why people take offense to being called a machine, and I'm trying to explain that. But to understand this we have to understand that there isn't a singular objective way to interpret statements. We can agree that language is fuzzy, right?
So let me try to translate, again.
You say: "People are machines"
(Many) People hear: "People are mechanical automata, running pre-defined routines"
I hear you, this is not what you are trying to communicate. That's not what you want them to hear. But if you want them to hear what you actually mean it is very helpful to understand that some people will hear something different.
Why do they hear the other thing? Because they don't have intimate familiarity with machines and how general that word is. *You have a better understanding of what a machine is than most people.* That's likely the cause for miscommunication.
When they think of a machine they think of things like a car, a computer, a blender, a TV, an oven, or a multitude of other similar things. Even if some of these use probabilistic programming, the average person is not going to know what probabilistic programming even is. They just see something mechanical. Deterministic.
I'm sure you know this, but it is worth reiterating. Communication has 3 main components: What you intend to communicate, the words/gestures/etc you use to communicate, and what the other person hears. Unfortunately (fortunately?) we can't communicate telepathically, so don't forget that the person you're talking to can have a reasonable interpretation that is significantly different from what you intended to say.
When talking about people who are not mathematicians or computer scientists, on average, yes absolutely they hear something like that when told humans are machines.