| ▲ | kmeisthax 2 days ago |
| Because that path lies skill atrophy. AI research has a thing called "the bitter lesson" - which is that the only thing that works is search and learning. Domain-specific knowledge inserted by the researcher tends to look good in benchmarks but compromise the performance of the system[0]. The bitter-er lesson is that this also applies to humans. The reason why humans still outperform AI on lots of intelligence tasks is because humans are doing lots and lots of search and learning, repeatedly, across billions of people. And have been doing so for thousands of years. The only uses of AI that benefit humans are ones that allow you to do more search or more learning. The human equivalent of "inserting domain-specific knowledge into an AI system" is cultural knowledge, cliches, cargo-cult science, and cheating. Copying other people's work only helps you, long-term, if you're able to build off of that into something new; and lots of discoveries have come about from someone just taking a second look at what had been considered to be generally "known". If you are just "taking shortcuts", then you learn nothing. [0] I would also argue that the current LLM training regime is still domain-specific knowledge, we've just widened the domain to "the entire Internet". |
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| ▲ | gtirloni 2 days ago | parent | next [-] |
| Here on HN you frequently see technologists using words like savant, genius, magical, etc, to describe the current generation of AI. Now we have vibe coding, etc. To me this is just a continuation of StackOverflow copy/paste where people barely know what they are doing and just hammer the keyboard/mouse until it works. Nothing has really changed at the fundamental level. So I find your assessment pretty accurate, if only depressing. |
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| ▲ | mirsadm 2 days ago | parent [-] | | It is depressing but equally this presents even more opportunities for people that don't take shortcuts. I use Claude/Gemini day to day and outside of the most average and boring stuff they're not very capable. I'm glad I started my career well before these things were created. |
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| ▲ | tombert 2 days ago | parent | prev | next [-] |
| > Because that path lies skill atrophy. Maybe, but I'm not completely convinced by this. Prior to ChatGPT, there would be times where I would like to build a project (e.g. implement Raft or Paxos), I write a bit, find a point where I get stuck, decide that this project isn't that interesting and I give up and don't learn anything. What ChatGPT gives me, if nothing else, is a slightly competent rubber duck. It can give me a hint to why something isn't working like it should, and it's the slight push I need to power through the project, and since I actually finish the project, I almost certain learn more than I would have before. I've done this a bunch of times now, especially when I am trying to directly implement something directly from a paper, which I personally find can be pretty difficult. It also makes these things more fun. Even when I know the correct way to do something, there can be lots of tedious stuff that I don't want to type, like really long if/else chains (when I can't easily avoid them). |
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| ▲ | scellus 2 days ago | parent | next [-] | | I agree. AI has made even mundane coding fun again, at least for a while. AI does a lot of the tedious work, but finding ways to make it maximally do it is challenging in a new way. New landscape of possibilities, innovation, tools, processes. | | |
| ▲ | tombert 2 days ago | parent [-] | | Yeah that's the thing. Personal projects are fun for the same reason that they're easy to abandon: there are no stakes to them. No one yells at you for doing something wrong, you're not trying to satisfy a stakeholder, you can develop into any direction you want. This is good, but that also means it's easy to stop the moment you get to a part that isn't fun. Using ChatGPT to help unblock myself makes it easier for me to not abandon a project when I get frustrated. Even when ChatGPT's suggestions aren't helpful (which is often), it can still help me understand the problem by trying to describe it to the bot. |
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| ▲ | Nathanba 2 days ago | parent | prev [-] | | true and with AI I can look into far more subjects more quickly because the skill that was necessary was mostly just endless amounts of sifting through documentation and trying to find out why some error happens or how to configure something correctly. But this goes even further, it also applies to subjects where I couldn't intellectually understand something but there was noone to really ask for help. So I'm learning knowledge now that I simply couldn't have figured out on my own. It's a pure multiplier and humans have failed to solve the issue of documentation and support for one another. Until now of course. I also think that once robots are around it will be yet another huge multiplier but this time in the real world. Sure the robot won't be as perfect as the human initially but so what. You can utilize it to do so much more. Maybe I'll bother actually buying a rundown house and renovating myself. If I know that I can just tell the robot to paint all the walls and possibly even do it 3 times with different paint then I feel far more confident that it won't be an untenable risk and bother. |
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| ▲ | Workaccount2 2 days ago | parent | prev [-] |
| >Because that path lies skill atrophy. I wonder how many programmers have assembly code skill atrophy? Few people will weep the death of the necessity to use abstract logical syntax to communicate with a computer. Just like few people weep the death of having to type out individual register manipulations. |
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| ▲ | cmsj 2 days ago | parent | next [-] | | I would say there's a big difference with AI though. Assembly is just programming. It's a particularly obtuse form of programming in the modern era, but ultimately it's the same fundamental concepts as you use when writing JavaScript. Do you learn more about what the hardware is doing when using assembly vs JavaScript? Yes. Does that matter for the creation and maintenance of most software? Absolutely not. AI changes that, you don't need to know any computer science concepts to produce certain classes of program with AI now, and if you can keep prompting it until you get what you want, you may never need to exercise the conceptual parts of programming at all. That's all well and good until you suddenly do need to do some actual programming, but it's been months/years since you last did that and you now suck at it. | |
| ▲ | kmeisthax 2 days ago | parent | prev [-] | | Most programmers don't need to develop that skill unless they need more performance or are modifying other people's binaries[0]. You can still do plenty of search-and-learning using higher-level languages, and what you learn at one particular level can generalize to the other. Even if LLMs make "plain English" programming viable, programmers still need to write, test, and debug lists of instructions. "Vibe coding" is different; you're telling the AI to write the instructions and acting more like a product manager, except without any of the actual communications skills that a good manager has to develop. And without any of the search and learning that I mentioned before. For that matter, a lot of chatbots don't do learning either. Chatbots can sort of search a problem space, but they only remember the last 20-100k tokens. We don't have a way to encode tokens that fall out of that context window into some longer-term weights. Most of their knowledge comes from the information they learned from training data - again, cheated from humans, just like humans can now cheat off the AI. This is a recipe for intellectual stagnation. [0] e.g. for malware analysis or videogame modding |
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