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This argument can be applied to anything AI does. AI can do bad writing, bad code, bad graphics and bad music. But AI cannot (yet?) do the job of a skilled wri

by GuB-42 1mo ago

This argument can be applied to anything AI does. AI can do bad writing, bad code, bad graphics and bad music. But AI cannot (yet?) do the job of a skilled writer, coder, graphical artist and musician. And it is the same problem every time, LLMs lack intention. That's essentially what the article is about, writers choose every word because they have something to convey. Something complex, deliberate, that can't fit in a simple prompt, a LLM can't get these nuances, it is all in the writer's head, so you get something generic, the information to do it better simply isn't there. But it apply to other arts as well, ChatGPT flyers, Suno music, etc.. they all look and sound the same, because there is no intention behind them, besides all the technical issues, like inconsistent images and instruments blending into each others, the model just can't work with information it doesn't have, so it just generate something generic that looks like its training dataset. And it is the same with code. Coding is not about the programming language, it is about expressing with precision what the machine has to do, and programming languages are really good at that, that's why they exist. LLMs let you use English instead, but it doesn't change the fact that everything has to be intentional, otherwise, the LLM will just put something that may or may not be what you want. Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests.

AdieuToLogic 1mo ago
This is because understanding is an intrinsically personal experience. To convey it to others is to choose words, phrasing, and sentences which best express what is in one's mind. Call it "intention", call it "understanding", call it "effective communication." The lack thereof is obvious and easily identified. > Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests. Another way to phrase this is: Because someone already thought about the problem and what needs to exist in order to solve it.
NewsaHackO 1mo ago
Also, a huge area that AI seems to thrive in is cybersecurity, which almost by definition involves errors that the original programmer failed to think of or catch.
fennecfoxy 1mo ago
I mean a lot of it comes down to: "Give me a poster for my band playing a gig" Versus "Give me a poster for my band playing a gig, it should have x y and z. Use a x' artistic style and include elements of y'. The layout should be z'..." You ask for the default, you get the default.
- GuB-42 1mo ago
  The thing is, at some point, it takes so much work telling the AI exactly what to do that you are better off doing the damn thing yourself. AI can help with the execution, and for an amateur, this is important. But for real pros, the ones who actually know the appropriate style and what the layout should be, they usually have the execution nailed down. Prompting will likely drag them down, if they use AI, it is more likely to be in the form of "augmenter" tools: upscaling, content-aware fill, etc... Again, same idea with code. Programming languages are only an issue for inexperienced coders, for those who really know what they are doing, it is usually second nature, and they may be better served writing the code themselves than trying to get a LLM to do it. Again, AI has its use: completion, analysis, etc... That's also the reason why I believe that so many people are missing the point with generative AI taking jobs. Because they are not in the field, they only see the execution, image editing software, DAWs and programming languages look arcane, they think it is what takes the most skills, and that if you can get over it using AI, you can do just as well. The truth is that it is not the case, not by a long shot, execution is just the first step. It is a problem for juniors however. Juniors are at the first step, they have the execution but not much more, they need to grow real skills, but how will they grow these skills if no one want them because they are at the level where AI can do most of their job.
- al_borland 1mo ago
  Many people go to professionals because they don't know what those x, y, and z are. They don't have the experience, the vision, the taste, or the language to convey what they want. They need someone else with those things to do it for them. Proficiency with the tools (pencil, brush, instrument, etc) is only half the equation. The other half is what to do make and what to express. Most non-artists are bad at both. Others are proficient with the tools, but have no vision, so they help produce other people's visions. AI might be able to help someone with vision who lacks proficiency with the tools, but I suspect that's a small minority of people.

by GuB-42 1mo ago

AdieuToLogic 1mo ago

This is because understanding is an intrinsically personal experience. To convey it to others is to choose words, phrasing, and sentences which best express what is in one's mind. Call it "intention", call it "understanding", call it "effective communication." The lack thereof is obvious and easily identified. > Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests. Another way to phrase this is: Because someone already thought about the problem and what needs to exist in order to solve it.

NewsaHackO 1mo ago

Also, a huge area that AI seems to thrive in is cybersecurity, which almost by definition involves errors that the original programmer failed to think of or catch.

fennecfoxy 1mo ago

I mean a lot of it comes down to: "Give me a poster for my band playing a gig" Versus "Give me a poster for my band playing a gig, it should have x y and z. Use a x' artistic style and include elements of y'. The layout should be z'..." You ask for the default, you get the default.

GuB-42 1mo ago
The thing is, at some point, it takes so much work telling the AI exactly what to do that you are better off doing the damn thing yourself. AI can help with the execution, and for an amateur, this is important. But for real pros, the ones who actually know the appropriate style and what the layout should be, they usually have the execution nailed down. Prompting will likely drag them down, if they use AI, it is more likely to be in the form of "augmenter" tools: upscaling, content-aware fill, etc... Again, same idea with code. Programming languages are only an issue for inexperienced coders, for those who really know what they are doing, it is usually second nature, and they may be better served writing the code themselves than trying to get a LLM to do it. Again, AI has its use: completion, analysis, etc... That's also the reason why I believe that so many people are missing the point with generative AI taking jobs. Because they are not in the field, they only see the execution, image editing software, DAWs and programming languages look arcane, they think it is what takes the most skills, and that if you can get over it using AI, you can do just as well. The truth is that it is not the case, not by a long shot, execution is just the first step. It is a problem for juniors however. Juniors are at the first step, they have the execution but not much more, they need to grow real skills, but how will they grow these skills if no one want them because they are at the level where AI can do most of their job.
al_borland 1mo ago
Many people go to professionals because they don't know what those x, y, and z are. They don't have the experience, the vision, the taste, or the language to convey what they want. They need someone else with those things to do it for them. Proficiency with the tools (pencil, brush, instrument, etc) is only half the equation. The other half is what to do make and what to express. Most non-artists are bad at both. Others are proficient with the tools, but have no vision, so they help produce other people's visions. AI might be able to help someone with vision who lacks proficiency with the tools, but I suspect that's a small minority of people.