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Watching the Generative AI Hype Bubble Deflate
(ash.harvard.edu)
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this post was submitted on 22 Dec 2024
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Computers have always been good at pattern recognition. This isn't new. LLM are not a type of actual AI. They are programs capable of recognizing patterns and Loosely reproducing them in semi randomized ways. The reason these so-called generative AI Solutions have trouble generating the right number of fingers. Is not only because they have no idea how many fingers a person is supposed to have. They have no idea what a finger is.
The same goes for code completion. They will just generate something that fills the pattern they're told to look for. It doesn't matter if it's right or wrong. Because they have no concept of what is right or wrong Beyond fitting the pattern. Not to mention that we've had code completion software for over a decade at this point. Llms do it less efficiently and less reliably. The only upside of them is that sometimes they can recognize and suggest a pattern that those programming the other coding helpers might have missed. Outside of that. Such as generating act like whole blocks of code or even entire programs. You can't even get an llm to reliably spit out a hello world program.
Large context window LLMs are able to do quite a bit more than filling the gaps and completion. They can edit multiple files.
Yet, they're unreliable, as they hallucinate all the time. Debugging LLM-generated code is a new skill, and it's up to you to decide to learn it or not. I see quite an even split among devs. I think it's worth it, though once it took me two hours to find a very obscure bug in LLM-generated code.
If you consider debugging broken LLM-generated code to be a skill… sure, go for it. But, since generated code is able to use tons of unknown side effects and other seemingly (for humans) random stuff to achieve its goal, I'd rather take the other approach, where it takes a human half an hour to write the code that some LLM could generate in seconds, and not have to learn how to parse random mumbo jumbo from a machine, while getting a working result.
Writing code is far from being the longest part of the job; and you gingerly decided that making the tedious part even more tedious is a great idea to shorten the already short part of it…
It's similar to fixing code written by interns. Why hire interns at all, eh?
Is it faster to generate then debug or write everything? Needs to be properly tested. At the very least many devs have the perception of being faster, and perception sells.
It actually makes writing web apps less tedious. The longest part of a dev job is pretending to work actually, but that's no different from any office jerb.