5 ms·
What if useful AI is a fantasy?
- catlover76 2mo ago[dead]
- slimtrees 2mo agoSo-called "agentic" AI is definitely a fantasy. It's like saying a calculator can do your taxes. Doesn't work that way. But grifters gonna grift
- deleted 2mo ago[deleted]
- leothetechguy 2mo agoDefinitely a fantasy, just one that people try to realize at the moment.
- geldedus 2mo agoTo me, it is as practical and concrete as it can be. Keep coping
- bluegatty 2mo agoIt's obviously useful - we have to figure out best practices.
- bigstrat2003 2mo agoIt is most certainly not obviously useful. To anyone who actually cares about quality and not just turning out slop, you have to spend so much time reviewing the code the machine generated that you wind up not saving any time. There are lots of people who don't give a damn about quality, but those were terrible developers before LLMs and remain so now.
- bluegatty 2mo agoIt's delusional for someone to contemplate that millions of developers out there are just churning out 'non usable stuff' and don't care about quality and that somehow you have some 'magic insight' they don't have. And lacking in self awareness to publicize that. Obviously some people are using it recklessly, it's the same with everything. Do you think it's more likely that 'the entire world is wrong and you are right' ... OR ... that you just personally have not figured out how to use the technology in way that makes sense and/or you have a bad sense of of what quality means in most contexts. AI produces easily 'better than human' code where it has a lot of guardrails, and is probably 10x better than humans at hunting down and fixing bugs. Software is 90% 'maintenance' , and a well maintained code base provide ample basis for the AI to understand what design and formatting to use for a given solution. It definitely falls down on it's own architecture, it's not that hard to work along with the AI. It doesn't matter what we think of Altman or whoever, or whatever or AGI or 'the bubble' - that's all noise. It's literally the most blatantly obvious 'useful' thing to happen to tech since the advent of machines - it takes a 'collapse of intellectual contextualization' to not realize that. You're watching cars replace horses, they are not the same thing.
- AnimalMuppet 2mo ago> Do you think it's more likely that 'the entire world is wrong and you are right' ... OR ... that you just personally have not figured out how to use the technology in way that makes sense and/or you have a bad sense of of what quality means in most contexts. Yeah, see, I've seen this movie before. I've seen it with Lisp. "You just haven't used it enough to reach enlightenment! We all have! Keep going; you'll see it too!" And then with Haskell. Exact same looking down on everyone who doesn't agree as unenlightened, as people who Just Don't Get It. Both Lisp and Haskell are useful languages. Neither is the future of mainstream programming, not just because the mainstream is unenlightened, but because those languages don't fit the way most programmers think. People are different. Different languages fit different people. If Lisp fits how you think, when you find it after wandering through procedural languages, it feels incredibly freeing. But if it doesn't fit... So I get very nervous about "you just haven't figured out how to use it" claims. Maybe it's true. Or maybe it just doesn't fit a bunch of people, and browbeating them with claims that they're unskillful does not make it fit them any better.
- skybrian 2mo agoThe hypothetical is that everyone will eventually agree with the author that AI is not useful. I don't see what could possibly change everyone's minds at this point. People have too much direct experience with it. At best, it might remain controversial.
- kennyadam 2mo agoAnecdotally, my 81 year old father was able to point his phone at the boiler and ask Gemini what the error message meant. It correctly identified the boiler model, identified the error code being displayed on the screen, explained what it meant, provided him with a way to confirm the problem by checking the water pressure guage and then asked to be shown the underside. It again correctly identified and described to him the position and colour of the filling loop lever and how to adjust it to start and stop the water flow. He was able to do all this instead of spending hundreds on getting a plumber out at night because it was during a cold spell and he needed the heating on. That kind of thing is no fantasy and was amazing to witness. edit: I had already looked up the error code the "old fashioned" way using Google to find the boiler manual, so I would have stepped in if needed, but it was literally flawless and I can't think of any time anything like that hasn't worked when I've used it for similar diagnostics.
- chrisjj 2mo ago> That kind of thing is no fantasy and was amazing to witness. How about the case where the "AI" misided the error code? Did you test that? Result could be even more amazing... > He was able to do all this instead of spending hundreds on getting a plumber out at night ... or consulting the manual.
- throw310822 2mo agoSeems we are many to have had the exact same experience with the boiler and an LLM (Claude in my case). +1.
- FloorEgg 2mo agoUsefulness depends on intended job to be done. A hair dryer isn't very useful at drying clothes. If someone spent a lifetime mastering woodworking with hand tools, and then was shown a couple very early rudimentary power tools (lacking safety features, crude features, etc) they would rightly conclude they weren't useful. The artisan can do better work faster with less risk of dismemberment without them. Prior to LLMs, the world's demand for good software was bottlenecked by access to competent software engineers. The people who want software just want it, they don't care about the craft. They have a different job to be done than the engineer. An example this reminds me of is a jobs to be done theory thought exercise: Two different first time home owners need to store yard working tools in their backyard, and determine they need a shed. The first one cares most about minimizing the time it takes to get the shed. The second one has some special constraints to deal with AND also wants to start developing their amateur construction skills. They both need sheds, but they have different values, so: - the first one buys a shed-kit made of plastic panels that can easily be assembled in 20 minutes. - the second one buys a power saw, power drill, tool belt, saw horses, lumber, screws, metal roofing, etc and builds a custom shed from relative scratch over a few weekends. Another example is getting take out vs cooking the meal yourself. There are many many examples. LLMs are already useful to many. They are also not useful to many others. To assume they aren't useful to anyone just because they aren't useful to you is a sign of absent cognitive empathy. Not acknowledging that other people have other priorities and values they are equally valid to your own.
- hermitShell 2mo agoThe author of the article mainly talks about agentic programming, code generation, and reasoning. Ans very rightly identifies a big problem with agentic programming, in my experience. If developers can't maintain the software without AI, it's doubtful they can steer AI to maintain it either. Maybe this is not true and we can tell AI something like 'reduce the number of lines of code' until the essential software is exposed and pared down to a quantity and modularity that humans can then participate. No doubt, most of the value creation is outside of creating software. But if Nvidia and Anthropic do succeed in making better hardware and better software, then the positive reinforcement loop does seem like it could take off. And coding is a big part of that. Maybe we don't need to understand the code at all? Hard to fathom.
- 3dedb728-3f77 2mo agoUseful AI is. Useful LLM is not.
- mike_hock 2mo ago> What if <common sense>? I find it baffling that some people had to find this out the hard way. You already knew that it's — if not more work — then at least more tedious to study existing code than write your own. People have been choosing greenfield rewrites over grokking legacy code since forever.
- chrisjj 2mo agoWe can already see (net) useful so-called AI is more than a fantasy. It's a psychotic delusion.
- hosel 2mo agoI seriously don’t understand the naysayers around here. Have they just not used anything past gpt4? You can’t just outsource all of your thinking to them, but they’re obviously useful.
- jkahrs595 2mo ago> At first this seems far-fetched, but consider what happened to Facebook’s Metaverse. For a brief window of time it actually seemed reasonable to believe that we would all be spending most of our waking hours with high-tech ski goggles strapped to our heads. That we would work, relax, and socialize with these bulky headsets tricking our brains into thinking they were in a different world. Literally nobody thought this.
- derdi 2mo ago> I didn’t have a mental model for the thing that was in front of me. If there is a bug, or if a new feature needed to be added my mind was precisely where it was before I started prompting, and I couldn’t even begin to make changes until I had built a thorough understanding of the code. Yes. Like working in a team. It can be hard to work on a team and to have to understand what your colleagues did, and how to fix or extend it. What if working in teams is a fantasy?
- ilaksh 2mo agoIt's so interesting that people are so divided on this. He even said he generated multiple applications. Yet he has found a way to just about dismiss it somehow. AI is not going to go away and it's not going to stop improving. That would go against the entire history of computing. We have levels of improvements in the R&D pipeline in every area: hardware, software, model architecture and training. The models will get larger, architecture more sophisticated, computation dramatically more efficient. New materials, paradigms, more efficient nano-devices, scaling up manufacturing for better devices that are already out of the lab, etc. are in progress pointed towards multiple orders of magnitude efficiency gains. And by the way, that is not at all unusual -- we have been making large and small innovations in computing efficiency for decades. There are still some things lacking in AI -- it still is jagged intelligence. Give it a few years, people will be nostalgic about the time when humans could still point to some victories here and there. That doesn't require any major breakthroughs -- just continuing to increase the size of the models and improving the training.
- wizzledonker 2mo agoI guess, just to play devils advocate, what if code turns out to just be the minimally expressive communication medium required for a human to maintain agency over the function of a system? If we consider (and I’m not saying this is true, just for arguments sake) that this agency is important as other humans enjoy talking to humans about a goal, rather than machines, and we think this will never change. In this peculiar case, it actually doesn’t matter how “good” llms get - they will never cross a barrier fundamental to human nature?
- ilaksh 2mo agoMaybe you're trying to argue that LLMs won't be able to simulate humans or reproduce all of human nature. That's true, but it's not what I was discussing. I was talking about programming. Also, they are really VLMs and VLAs and there are other types of architecture and there will be many more. So if you think that there is something salient about humans that can't be reproduced eventually by AI, then look into religious dualism.
- CM30 2mo agoPersonally, I've found that understanding what the AI generates well enough to make substantial changes to it hasn't been too difficult, though it'll obviously depend on how complex the project you're working on is. Effectively speaking, it's like using any sort of off-the-shelf solution and then modifying that solution; you don't need to understand it to use it for your project, but you'll need to do so to make significant changes or add extra functionality. Practically speaking, is there really a difference between prompting an LLM to create a CMS for a website and installing something like WordPress or Ghost? The setup requires no understanding of the underlying software, but you'll have to build up a mental model from scratch if you want to extend or modify it later. Of course, it's not going to please anyone that likes the process of programming or knows enough to tell that the output is mediocre at best. But it's very useful for people that don't know how something works and want a 'workable' solution that functionally does what they need. It's basically the next iteration of the WYSIWYG web design tool, the CMS, the site builder, etc. A professional software engineer would be horrified by the code they output, but a non-technical manager type wouldn't notice or care.
- xyzzy123 2mo ago> Practically speaking, is there really a difference between prompting an LLM to create a CMS for a website and installing something like WordPress or Ghost? There is some difference; when you install WordPress or Ghost, your problems are shared. There's a community that goes along with the software and a "shared understanding in the world" of how it works and where the rough edges and limitations are. A lot of the time, LLMs will actually be better at modifying WordPress or Ghost to do what you want than they will be at fixing the CMS you built last Tuesday. When you custom build, you can get an exact fit for your needs but your misery is yours alone.
- xyzzy123 2mo agoThe problem he's describing comes up any time you have a team of developers. That doesn't mean the usefulness of teams is a fantasy because you didn't write all the code yourself. If you don't have a useful mental model of the architecture that's a communication / review / documentation problem, not a problem with the entire idea of codegen.
- monkeydreams 2mo agoAI has useful features but the majority of use cases are not useful but are thrust upon us as an excuse to extract more data. Even if the worst happens in the AI market some uses will still remain. Far fewer, I suspect, than will be demand the computational capacity of all the DCs popping up everywhere.
- erelong 2mo agoSounds like author is currently at the point of learning to use AI to develop mental models (simply continue?) I think one of the issues with LLMs that confuses people is that they're such a broad open-ended tool that people don't know what to do with them and so conclude they're not sure if they are useful, but in a meta way you could just keep asking the AI questions like "how do I make good use of LLMs in this case" and so on They seem like an upgraded kind of search engine for text prompts, if nothing else
- teravor 2mo agoto maintain a mental model of LLM generated code I resort to exclusively DOD (data oriented design) principles. I spend most of my time engineering structs and describing transitions in English then have the LLM execute on the transitions and whatever scaffolding (eg. async runtimes, external libraries) are required. it usually helps if you know how something is to be done, you just want to save time not doing it yourself. this way you can give the LLM intermediate structs and transitions to work with, and constrain it this way not to do something stupid.