3 ms·

I'm sure this article resonates with many people; it doesn't resonate with me. I get value out of (and even enjoy) lots of software, commercial and otherwise (

• bevr1337 1y ago
  > As long as the benefits outweigh the hazards, I use it. You and the author may be in agreement but with differing risk tolerance. > Ironically, the best answer to many of the article's suggestions... is to write your own software with LLMs. I don't think it's ironic but I do think it's false. How do LLMs satisfy a single requirement from the author's punchline list?
  • nothrabannosir 1y ago
    LLMs don’t but the problems you write for yourself using LLMs, do.
  • GMoromisato 1y ago
    > You and the author may be in agreement but with differing risk tolerance. I agree. And I'm not saying the author is wrong--they have their preferences. I'm just saying that for me the benefits outweigh the risks, and I'm betting most people are like me (at least outside HN). > I don't think it's ironic but I do think it's false. How do LLMs satisfy a single requirement from the author's punchline list? The main suggestion from the author is to write your own custom software tuned to your needs instead of relying on a mass-market, one-size-fits-all piece of complex, expensive software that has to be monetized by dark patterns. I guess in a world where everyone knows how to program, and has the time and desire to do so, that would work. But in the real world, the only way to get the bulk of humanity to write their own software is with LLMs. I think it's ironic because I bet the author does not like LLMs.
    • akkartik 1y ago
      Don't bet too much, because I'm still undecided on LLMs. Interestingly, I have no memory of ever thinking about LLMs as I wrote this. Part of it is I slaved over this talk a lot more than my usual blog posts, for about six months, after starting the initial draft in Dec 2022 (https://akkartik.name/post/roundup22 https://akkartik.name/post/roundup22). ChatGPT came out in Nov 2022. So I was following (and starting to get annoyed by) the AI conversations in parallel with working on this talk, but perhaps they felt like separate threads in my head and I hadn't yet noticed that they can impact one another. These days I've noticed the connections, and I feel the pressure to try to rationalize one in terms of the other. But I still don't feel confident enough to do so. And my training has always emphasized living with ambiguity until one comes up with a satisfying resolution. It took us 200 years from the discovery of telescopes[1] to attain some measure of closure on all the questions they raised. There's no reason to think the discovery of LLMs will take any less time to work through. They'll still be remembered and debated in a hundred years. Your hot takes or mine about LLMs will be long forgotten. In the meantime, it seems a good idea for me to focus on what I seem uniquely qualified to talk about. [1] https://web.archive.org/web/20140310031503/http://tofspot.blogspot.com/2013/08/the-great-ptolemaic-smackdown.html https://web.archive.org/web/20140310031503/http://tofspot.bl... is a fantastic resource.
      • GMoromisato 1y ago
        > And my training has always emphasized living with ambiguity until one comes up with a satisfying resolution. I wish more people had this attitude, particularly towards LLMs. We're at an interesting point in time where we don't know how LLMs will evolve. Maybe we've hit the plateau and LLMs won't get any better. Even in that case, it will take decades for their effect to be felt in the entire industry, much less the world. Or maybe they will continue to improve on their way to ASI. My point, though, is that if you're worried about user control over their computing environment (which I 100% understand), then LLMs might be the best solution. I think they could be the only practical solution, as all others seem like pipe dreams.
        • akkartik 1y ago
• safety1st 1y ago
  The fundamental tradeoff a lot of consumer software seems to be based on these days is they will offer you stuff you want (i.e. be feature rich), in exchange for stuff you don't (i.e. steal your data, show you ads). Whereas a FOSS author is a lot more likely to take the "do one thing well" approach. What I settled for was an approach where I try to minimize the use of commercial software in my personal life, but in my business if we need what the commercial software does we'll just license it and get on with things. For the most part in my life I don't really NEED some feature or another, it might be nice to have, but with any type of commercial software or service there's always going to be the risk that they'll push some update that shoves ads down my throat or introduces microtransactions or something, so I'm OK to just go without and use the FOSS alternative. In business though, we'll be at a competitive disadvantage if I force everyone to use only FOSS. There are many times where I've looked at the open source equivalent of some big SaaS and it was just going to be more work to set up and maintain a less featureful open source equivalent. So, I'm more inclined to do a deal with the devil because at the end of the day our time and resources need to be focused elsewhere.
  • gsf_emergency_2 1y ago
    That's because (on paper) B2Bs get much more out of their clients (sorry!)
• maegul 1y ago
  > Ironically, the best answer to many of the article's suggestions (thousands rather than millions, easy to modify, etc.) is to write your own software with LLMs. Not sure exactly irony you mean here, but I’ll bite on the anti-LLM bait … Surely it matters where the LLM sits against these values, no? Even if you’ve got your own program from the LLM that’s yours, so long as you may need alterations, maintenance, debugging or even understanding its nuances, the nature of the originating LLM, as a program, matters too … right? And in that sense, are we at all likely to get to a place where LLMs aren’t simply the new mega-platforms (while we await the year of the local-only/open-weights AI)?
  • GMoromisato 1y ago
    > Surely it matters where the LLM sits against these values, no? Yes, I agree, but it's all trade-offs. The core problem is this: 1. Software is very expensive to write 2. So, you need to sell to as many people as possible 3. So, you need to add lots of features to attract as many people as possible 4. And you need to monetize it with ads, data-selling, and SaaS subscriptions. 5. But that makes software complicated, brittle, and frustrating. LLMs can break the cycle if they make it cheap to write software. Instead of buying a mass-market product with 10x more features than you need, you create custom software that does exactly what you need and no more. But aren't we trading one master of another? Instead of bowing down to Microsoft/Meta/Google, we bow down to OpenAI/Anthropic/Meta/Google? Maybe, but when an LLM writes code for you, you own the code. The code runs outside of the LLM (usually) on an open platform. But what if you have to modify the code? Then you ask an LLM (maybe not the original LLM) to modify the code. That's far easier than asking Google to modify Gmail. If you believe in the suggestions of the author, then I don't think there is a better answer than LLMs. We don't live in a world where everyone can solve their software problems by forking some code, much less modifying it themselves. And the reason I think it's ironic is because I suspect the author hates LLMs.
    • akkartik 1y ago
      > 1. Software is very expensive to write I disagree with this, right at the start. I think software is cheap to write but expensive to maintain when you try to sell to as many people as possible. It's the OpEx that kills you, not the CapEx. I go into this more in the current state of https://akkartik.name/about https://akkartik.name/about So I wrote OP to encourage more exploration of the alternative path. If you build something and don't keep adding features to it in a futile attempt at land-grabbing "users" who will for the most part fail to pay you back for the over-investment your current VC-based milieu causes you to think is the only way to feel a sense of meaning from creating software -- if you don't keep adding features to it and you build on a substrate that's similarly not adding features and putting you on a perpetual treadmill of autoupdates, then software can be much less expensive. I plan to just put small durable things out into the world, and to take a small measure of satisfaction in their accumulation over the course of my life. The ideal is a rock: it just sits inert until you pick it up, and it remains true to its nature when you do pick it up. > LLMs can break the cycle if they make it cheap to write software. Instead of buying a mass-market product with 10x more features than you need, you create custom software that does exactly what you need and no more. That's the critical question, isn't it. Will LLMs yield custom software that does exactly what you need and stabilizes? Or will they addict people to needing to endlessly tweak their output so AI companies can juice their revenue streams? What skills does it take to nudge an LLM to create something durable for you? How much do people need to know, what skills do they need to develop? I don't know, but I feel certain that we will need new skills most people don't currently have. Another way to rephrase the critical question: do you trust the real AIs here, the tech companies selling LLMs to you. Will the LLMs they peddle continue to work in 10 years time as well as they do today? If they enshittify, will you be prepared? Me, I'm deeply cynical about these companies even as LLMs themselves feel like a radical advance. I hope the world will not suffer from the value capture of AI companies the way it has suffered from the value capture of internet companies.
• gsf_emergency 1y ago
  >I get value out of That's the rub. Does it benefit the developers much more than the users, in aggregate? It's not an easy question to answer even for vaccines.. But I'd wager it's a no, because, e.g. Pfizer(plus or minus BioNTech) probably could not have learnt enough* from their deployment.. *I.e. gain nonfungible knowhow