5 ms·

The eloquence with which this point gets (repeatedly) made is continuing to improve each next time I read it. However, I still feel like we haven't nailed it. T

• xnx 5mo ago
  This concept won't reach that point because when you chisel too hard it crumbles. There are countless lower level tasks that typical programmers no longer learn how to do. Our capacity for knowledge is not unlimited so we offload everything we can to move to the next level of abstraction.
  • ua709 5mo ago
    I get your point, I just wonder how accurate it is. We basically never look at the output of the compiler, so I agree that tool allows one to operate at a higher level than assembly. But I always have to wade through the output from AI so I’m not sure I got to move to the next level of abstraction. But maybe that’s just me.
    • willhslade 5mo ago
      Are compilers deterministic?
      • 23df 5mo ago
        For all intents and purposes yeh. Its really about the variance in actual outcomes vs the expected. The variance is not much is it? With LLMs that absolutely isnt the case.
      • ua709 5mo ago
        I'm sure someone, somewhere, once wrote one that wasn't but in general, yes they are. The ones I use certainly are. And with a bit of training you can reason and predict how they will respond to a given input with a large degree of accuracy without being familiar with how the particular compiler under question was implemented. Not so with the AI tools. At least with the ones I use anyway.
      • dbalatero 5mo ago
        Given the same compiler, I believe they would be the same between runs given the same inputs. I suppose that could not be true at the margins, but I would expect correctness out of whatever path it chose.
      • SkyBelow 5mo ago
        Technically LLMs can be ran in deterministic mode as well, but I don't think that is enough. Even a deterministic LLM is too chaotic, small changes in prompts or the otherwise general context can result in vastly different outputs. This makes me think we need some other factor that is stronger than (or maybe orthogonal to) determinism. A notion of being well-behaved or some other non-chaotic term, so that slightly different inputs don't lead to vastly unexpected results. Even that doesn't feel quite correct, because a compiler does seem quite chaotic. Forget a semi colon and an otherwise 99.99% code base results in a vastly different output. But it is still a very understandable output. Very predictable. So while treating both compilers and LLMs as functions that map massive input strings to massive output strings, there is some property I can't well define that compilers have that LLMs still lack (and the question is if they'll always lack it). I can't really define what it is, but it is something more than determinism.
  • staticshock 5mo ago
    That's true, but I think it's beside the point. The flip side of that argument, which is equally true, goes something like, "not doing cognitive push-ups leads to cognitive atrophy." There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators), primarily because those are well bounded domains, so we understand the nature of the codependency we're signing up for. AI is an amorphous and still growing domain. It is not a specific rung in the abstraction hierarchy; it is every rung simultaneously, but at different fidelity levels.
    • koshyjohn 5mo ago
      > "not doing cognitive push-ups leads to cognitive atrophy" This is one of the points being made in the post, at least in reference to people who already have some mastery of their craft. If they outsource their thinking without elevating it, they aren't exercising that metaphoric muscle between their ears.
    • kochikame 5mo ago
      > There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators) I'd argue these are not at all OK to lose. You live in an earthquake zone? You sure better know which way is north and where you have to walk to get back home when all the lines are down after a big one. You need to do a quick mental check if a number is roughly where it should be? YOu should be able to do that in your head. There might be better examples that support your point more effectively e.g. cursive writing
      • staticshock 5mo ago
        Yep, there are tons. Growing food, building shelter, etc. But, for pretty much all of the skills we've allowed to atrophy in response to the advances of capitalism, technological & scientific progress, and societal changes, one COULD make the same basic argument, which is that losing that skill is detrimental to the individual, and yet here we are, not growing our own food, not building our own shelter, etc. The arguments you make ≤ the values you actually hold ≤ the actions you take in support of those values. I'm only interested in any such argument to the extent to which you've personally put it into practice. Otherwise, you're living proof of the argument's weakness. (To be fair, it's extremely hard to be internally consistent on this stuff! We all want better for ourselves than we have time and energy for. But that's my point: your fully subconscious emotional calculus will often undercut at least some of your loftier aspirations. Skills that don't matter anymore invariably atrophy due to the opportunity cost of keeping them honed.)
  • lsy 5mo ago
    AI coding isn’t an abstraction, though. You can’t treat a prompt like source code because it will give you a different output every time you use it. An abstraction lets you offload cognitive capacity while retaining knowledge of “what you are doing”. With AI coding either you need to carefully review outputs and you aren’t saving any cognitive capacity, or you aren’t looking at the outputs and don’t know what you’re doing, in a very literal sense.
    • IceDane 5mo ago
      It's staggering to me how many times I've heard this argument that LLMs are just the next level of abstraction. Some people are even comparing them to compilers.
      • girvo 5mo ago
        > Some people are even comparing them to compilers. A lot of people are using them as such too: the amount of people talking about "my fleets of agents working on 4 different projects": they aren't reviewing that output. They say they are, but they aren't, anymore than I review the LLVM IR. It makes me feel like I'm in some fantasy land: I watch Opus 4.7 get things consistently backwards at the margins, mess up, make bugs: we wouldn't accept a compiler that did any of this at this scale or level lol
        • habinero 5mo ago
          Right? People have put in decades of work to make them extremely reliable, they didn't magically start like that.
        • IceDane 5mo ago
          It's awful, and seeing even engineers I respected become so AI pilled they're shipping slop without review has made me lose respect for them. It also can't help but make me wonder: what am I missing? Am I holding it wrong? Am I too focused on irrelevant details? So far, my conclusion is that while LLMs can be s productivity boost, you have to direct them carefully. They don't really care about friction and bad abstractions in your codebase and will happily keep piling cards on top of the crooked house of cards they've generated. Just like before AI, you need a cycle of building and refactoring running on repeat with careful reviews. Otherwise you will end up with something that even an LLM will have a hard time working in.
  • imiric 5mo ago
    The idea that a tool intended to replace all human cognitive work is the next level of abstraction is so fundamentally flawed, that I'm not sure it's made in good faith anymore. The most charitable interpretation I can think of is that it's a coping mechanism for being made redundant. Nevermind the fact that these tools are nowhere near as capable as their marketing suggests. Once companies and society start hitting the brick wall of inevitable consequences of the current hype cycle, there will be a great crash, followed by industry correction. Only then will actually useful applications of this technology surface, of which there are plenty. We've seen how this plays out a few times before already.
• ctvdev 5mo ago
  > That is, we are not yet at the "aphorism" stage of the discourse we learn by doing
  • ipython 5mo ago
    I’ve also seen along those lines “there is no compression algorithm for experience” - a nice summary of the hn posts from today.
    • skybrian 5mo ago
      It seems overly pessimistic about education. Book learning isn't everything, but a physics textbook could be seen as the compression of centuries of experience.
      • Ronsenshi 5mo ago
        Book learning to me seems like a compression of knowledge that had to be acquired through many years of experimentation and observation. But knowledge is not an experience itself. Take juggling for example - something that was on HN homepage last week. You can learn everything you need to know about juggling though a post or a book or an educational video. But can you juggle after all that book learning? Not at all - to be able to juggle one has to spend time practicing and no amount of reading can help meaningfully compress that process. Muscle memory required for juggling is not a 1:1 correlation to experience, but I feel like it's close enough to it.
        • ua709 5mo ago
          Juggling is a nice example. Maybe one could phrase it as, you can learn how to learn to juggle from a book.
        • ekeke 5mo ago
          Nice analogy. In many ways producing output of the brain is akin to juggling thoughts, ideas and concepts.
    • 5mo ago
• bla3 5mo ago
  > "can't make 9 babies in a month" It's "9 women can't make a baby in one month".
  • staticshock 5mo ago
    Hah, right, I mixed it up!
  • bluefirebrand 5mo ago
    In fairness, 9 women can't make 9 babies in a month either
    • gerdesj 5mo ago
      No idea why you were dv'd. It still takes roughly nine months to make a human baby, regardless of how many women or babies are involved!
      • bluefirebrand 5mo ago
        Sometimes HN doesn't like jokes, which is okay. I didn't really contribute much to discussion, so I probably deserve some downvotes. I'm ok with it.
        • Brajeshwar 5mo ago
          Actually, I like quite a lot of the subtle jokes on HN. It is harder to notice, fewer to find, and I don’t get it many a times. But when I get it (or someone explains it to me, perhaps out of pity), I chuckle, laugh, and laugh again. And I remember those comments.
          • godelski 5mo ago
            I think the occasional joke is fine but when you have too many then the comments get diluted. It's exactly that kind of thing that makes me hate Reddit and so many other places: spam.
• embedding-shape 5mo ago
  How about "Intelligence amplification, not artificial intelligence"? Also could be shortened to "IA, not AI", and gets even more fun when you translate it to Spanish: "AI, no IA".
• deleted 5mo ago
  [deleted]
• IceDane 5mo ago
  Outsource manual labor, not your brain.
  • sayYayToLife 5mo ago
    Both? I read pretty dense philosophy and the longer I live, the more I think the writers were just bad writers with good ideas. LLMs can convert poorly written sentences into clear sentences with examples.
• viccis 5mo ago
  >the medium is the message If you asked 100 Americans what this aphorism means, I strongly doubt a single one could capture McLuhan's original meaning.
  • apsurd 5mo ago
    You're right. ive struggled to understand what exactly this means, in large part perhaps it's so often misused? I think it means something like we're trapped in the constraints of the medium. Tweets say more about the environment of twitter than whatever message happened to be sent. but i think im off on that, ill look this person up and find out!
    • viccis 5mo ago
      It's confusing because "message" is not using its lay meaning, and decades of "medium" and "media" meaning drift meant that it isn't either. For "the medium is the message", "medium" refers to any tool that acts as an extension of yourself. TV is an extension of your community, even things like light bulbs (extends your vision) are included in his meaning. McLuhan argued that all forms of media like that carry a message that's more than just their content. "The message" in that argument refers to the message the medium itself brings rather than its content. For example, the airplane is "used for" speeding up travel over long distance, but the the message of its medium itself is to "dissolve the railway form of city, politics, and association, quite independently of what the airplane is used for." You can see it happening via online media that extend ourselves across the internet. Think of how, once easy video creation via Youtube became uniform, web comics stopped becoming a popular medium for comedy online. It's not like the web comics faded because they got worse; it's that they faded into a niche format because people didn't want to communicate via static images anymore. Or how, once short form videos on TikTok got big, you saw other platforms shift to copy the paradigm. McLuhan's point is that it's not just the content of those short form videos that matters; it's the message of the format itself. Peoples' attention spans grow shorter because of the format, and before too long, we saw the tastes and expectations of the masses change. Reddit's monosite-with-subcommunities format and dopamine triggering voting feedback mechanism were its message more than any actual content posted there, and it's why traditional forums are niche and dwindling. If you want to get a pretty good understanding of it, just read the first chapter from his book Understanding Media. It's short and relatively straight forward.
• thomastjeffery 5mo ago
  Meaning is abstract. We can't express meaning: we can only signify it. An expression (sign) may contain the latent structure of meaning (the writer's intention), but that structure can only be felt through a relevant interpretation. To maintain relevance, we must find common ground. There is no true objectivity, because every sign must be built up from an arbitrary ground. At the very least, there will be a conflict of aesthetics. The problem with LLMs is that they avoid the ground entirely, making them entirely ignorant to meaning. The only intention an LLM has is to preserve the familiarity of expression. So yes, this kind of AI will not accomplish any epistemology; unless of course, it is truly able to facilitate a functional system of logic, and to ground that system near the user. I'm not going to hold my breath. I think the great mistake of "good ole fashioned AI" was to build it from a perspective of objectivity. This constrains every grammar to the "context-free" category, and situates every expression to a singular fixed ground. Nothing can be ambiguous: therefore nothing can express (or interpret) uncertainty or metaphor. What we really need is to recreate software from a subjective perspective. That's what I've been working on for the last few years... So far, it's harder than I expected; but it feels so close.
  • rdevilla 5mo ago
    > Meaning is abstract. We can't express meaning: we can only signify it. An expression (sign) may contain the latent structure of meaning (the writer's intention), but that structure can only be felt through a relevant interpretation. I'm reminded immediately of the Enochian language which purportedly had the remarkable property of having a direct, unambiguous, 1-to-1 correspondence with the things being signified. To utter, and hear, any expression in Enochian is to directly transfer the author's intent into the listener's mind, wholly intact and unmodified: Every Letter signifieth the member of the substance whereof it speaketh. Every word signifieth the quiddity of the substance. - John Dee, "A true & faithful relation of what passed for many yeers between Dr. John Dee ... and some spirits," 1659 [0]. The Tower of Babel is an allegory for the weak correspondence between human natural language and the things it attempts to signify (as opposed to the supposedly strong 1-to-1 correspondence of Enochian). The tongues are confused, people use the same words to signify different referents entirely, or cannot agree on which term should be used to signify a single concept, and the society collapses. This is similar to what Orwell wrote about, and we have already implemented Orwell's vision, sociopolitically, in the early 21st century, through the culture war (nobody can define "man" or "woman" any more, sometimes the word "man" is used to refer to a "woman," etc). LLMs just accelerate this process of severing any connection whatsoever between signified and signifier. In some ways they are maximally Babelian, in that they maximize confusion by increasing the quantity of signifiers produced while minimizing the amount of time spent ensuring that the things we want signified are being accurately represented. Speaking more broadly, I think there is much confusion in the spheres of both psychology and religion/spirituality/mysticism in their mutual inability to "come to terms" and agree upon which words should be used to refer to particular phenomenological experiences, or come to a mutual understanding of what those words even mean (try, for instance, to faithfully recreate, in your own mind, someone's written recollection of a psychedelic experience on erowid). [0] https://archive.org/details/truefaithfulrela00deej/page/92/mode/2up https://archive.org/details/truefaithfulrela00deej/page/92/m...
• alphabeta3r56 5mo ago
  Taste/judgement cannot an AI beget
• nemomarx 5mo ago
  Isn't it the vehicle metaphor about bicycles for the mind? Not fully crystallized yet but I feel like someone will
• raincole 5mo ago
  "Bicycle of the Mind" has been cited to death. The problem is that it was coined so early that we are way past the aphorism stage now.
• billbrown 5mo ago
  AI is Augmenting (Actual) Intelligence.
• torben-friis 5mo ago
  I'm using "don't bring a forklift to the gym".
• jasondigitized 5mo ago
  Jobs had it right a long time ago. Its a bicycle for your mind.