This presupposes that there is some real and tangible benefit to LLMs, but an explanation of that argument is never put forward. Sure, the dream is to have the magic LLM genie write you code that runs perfectly and does what you want, but now you have code you didn’t write and can’t maintain. So you have to rely on the LLM genie for that to, and sooner rather than later - no matter how well you’ve trained it - it’s going to run across something it can’t do. And then what? You have a pile of code you don’t understand and no idea yourself how to fix it yourself because you kept having the genie do it.
What about all of that is worth the theft of the work of others, the resource demands to train and run the LLMs, and the debasement of actual coders?
There are certainly benefits to llms. Just the more casual interaction is one. This to me very much mirrors graphics as compared to terminal. many many things done on computers do not require graphics and can be done at the terminal but usage by ordinary folks increased with the advent of graphics systems and guis. graphics require more power but are a more user friendly interface. Similarly llms take more power than search queries but have a more user friendly interface. In addition it has generative capability allowing folks without significant talent to do some things they could not before. There are benefits but right now its a matter of if the benefits outweigh the costs. Seriously if this was graphics vs terminal the graphics basically double power usage when doing nothing in particular that need it. You start throwing a bunch of monitors up and it will bring it up significantly and actually using graphics like gaming and video go way more and it keeps increasing as we increase standar resolutions and what is considered normal performance. We would use way less power globally if folks only used computers at terminals and went back to listening to the radio.
A stark difference is that GUIs are designed with the same feature set as the CLI. Unlike an LLM, the GUI is not going to start suddenly making up data, offering nonexistent features, or straight up lying. The GUI is a more easily accessible interface that more or less behaves like the CLI. It’s like an orbital sander versus manual sanding - generally easier but you can also really fuck shut up if you don’t know what you’re doing.
Furthermore, coding is not merely clicking buttons or typing commands. You need to understand your language, your compiler, the intended runtime environment, etc., as well as best practices and then also have the purely human ability to create a new way of doing something. The LLM simply regurgitates what it’s been trained on without regard to the quality of that data - it can’t make value judgements on best approaches or even syntax, it’s just monkey-see, monkey-do. Hell, it can’t even sometimes differentiate between the correct syntaxes for different languages. In the end it gets you nothing but the illusion of convenience and the very real problem of non-functional, unmaintainable, and/or unoptimized code. It’s a fool’s bargain.
I think you are looking at llms in to large a context. Your issues you have with it are the same as search and if used as a further abstraction of search it is going to carry forward weaknesses. LLM’s trained more narrowly for specific purposes are going to do better if their narrow training data is of high quality rather than throwing everything at it.
This presupposes that there is some real and tangible benefit to LLMs, but an explanation of that argument is never put forward. Sure, the dream is to have the magic LLM genie write you code that runs perfectly and does what you want, but now you have code you didn’t write and can’t maintain. So you have to rely on the LLM genie for that to, and sooner rather than later - no matter how well you’ve trained it - it’s going to run across something it can’t do. And then what? You have a pile of code you don’t understand and no idea yourself how to fix it yourself because you kept having the genie do it.
What about all of that is worth the theft of the work of others, the resource demands to train and run the LLMs, and the debasement of actual coders?
There are certainly benefits to llms. Just the more casual interaction is one. This to me very much mirrors graphics as compared to terminal. many many things done on computers do not require graphics and can be done at the terminal but usage by ordinary folks increased with the advent of graphics systems and guis. graphics require more power but are a more user friendly interface. Similarly llms take more power than search queries but have a more user friendly interface. In addition it has generative capability allowing folks without significant talent to do some things they could not before. There are benefits but right now its a matter of if the benefits outweigh the costs. Seriously if this was graphics vs terminal the graphics basically double power usage when doing nothing in particular that need it. You start throwing a bunch of monitors up and it will bring it up significantly and actually using graphics like gaming and video go way more and it keeps increasing as we increase standar resolutions and what is considered normal performance. We would use way less power globally if folks only used computers at terminals and went back to listening to the radio.
A stark difference is that GUIs are designed with the same feature set as the CLI. Unlike an LLM, the GUI is not going to start suddenly making up data, offering nonexistent features, or straight up lying. The GUI is a more easily accessible interface that more or less behaves like the CLI. It’s like an orbital sander versus manual sanding - generally easier but you can also really fuck shut up if you don’t know what you’re doing.
Furthermore, coding is not merely clicking buttons or typing commands. You need to understand your language, your compiler, the intended runtime environment, etc., as well as best practices and then also have the purely human ability to create a new way of doing something. The LLM simply regurgitates what it’s been trained on without regard to the quality of that data - it can’t make value judgements on best approaches or even syntax, it’s just monkey-see, monkey-do. Hell, it can’t even sometimes differentiate between the correct syntaxes for different languages. In the end it gets you nothing but the illusion of convenience and the very real problem of non-functional, unmaintainable, and/or unoptimized code. It’s a fool’s bargain.
I think you are looking at llms in to large a context. Your issues you have with it are the same as search and if used as a further abstraction of search it is going to carry forward weaknesses. LLM’s trained more narrowly for specific purposes are going to do better if their narrow training data is of high quality rather than throwing everything at it.
Experience shows that more often than not it will just lie to you.