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Maybe I should just try it, but I don't feel like there are many situations where the process of "come up with a way to describe exactly what I want, generate i

Maybe I should just try it, but I don't feel like there are many situations where the process of "come up with a way to describe exactly what I want, generate it, and then debug the output until it works" would be faster than "just write it myself". And most of the ones I can think of would be in a situation where I'm working in an unfamiliar language/framework, and it's less about not having to type out the code and more about not having to context-switch to reference the docs for something I don't know off the top of my head Which- maybe that's just the thing, maybe that's what people are using this for right now (This could change once it gets to the point of stamping out entire projects, but for now)

CookieCrisp 4y ago
If you haven't tried it out, I recommend you do. I've been blown away with how much it will just get right. I started out giving it small tasks, but, I have continually been in a loop of "oh, I could have just asked it to do this larger task that contained the subtask I asked for, and it would have done it", because I keep thinking "surely it wont be able to do the whole thing", and each iteration I am asking it for more and more. As far as debugging, I find that I can just say "are there any bugs in that code?" and it does a great job at finding them if they're there (even though it's what it just gave me)
montecarl 4y ago
I'll give two examples of code I could for sure write myself but that I had gpt4 write for me because I figured it would be faster (and it was). The first one was to write a python script to watch a list of files given as cmd line arguments and plot their output anytime one of the files changed. It wrote a 100 line python script with nice argument parsing to include several options (like title and axes labels). It has one tiny bug in it that took a couple of minutes to fix. When I pointed out the bug it was able to fix it itself (had to do with comparing relative to abs file paths). If I wrote the script myself I would not have made something general purpose and it would have taken maybe 30 minutes to do. The second example required no fixing and appears bug free. I asked it to write a python function to take a time trace, calculate and plot the FFT, then apply FFT low pass filtering, and then also plot the filtered time signal vs the original. This is all straight forward numpy code but I don't work with FFTs often and would have had to lookup a bunch of different API docs. Way faster. I have also had it write some c macros for me, since complex C macros can be hard to escape properly and I'm not comfortable with the syntax. Its 100% successful there.
- brundolf 4y ago
  Yeah, so I think all of these fall under that category I mentioned (the first one may or may not for you, but it would for me because I don't work with Python much): most of the time saved is in looking up a bunch of things to assemble together, not ideating and writing out the logic. I can see this kind of codegen being useful in special situations, but it wouldn't really be useful in my day-to-day work because almost by definition I'm very familiar with the technologies I use every day
ben_w 4y ago
> come up with a way to describe exactly what I want This is the thing: you don't need to be exact. Even very vague gets a long way.
- deleted 4y ago
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CookieCrisp 4y ago

If you haven't tried it out, I recommend you do. I've been blown away with how much it will just get right. I started out giving it small tasks, but, I have continually been in a loop of "oh, I could have just asked it to do this larger task that contained the subtask I asked for, and it would have done it", because I keep thinking "surely it wont be able to do the whole thing", and each iteration I am asking it for more and more. As far as debugging, I find that I can just say "are there any bugs in that code?" and it does a great job at finding them if they're there (even though it's what it just gave me)

montecarl 4y ago

I'll give two examples of code I could for sure write myself but that I had gpt4 write for me because I figured it would be faster (and it was). The first one was to write a python script to watch a list of files given as cmd line arguments and plot their output anytime one of the files changed. It wrote a 100 line python script with nice argument parsing to include several options (like title and axes labels). It has one tiny bug in it that took a couple of minutes to fix. When I pointed out the bug it was able to fix it itself (had to do with comparing relative to abs file paths). If I wrote the script myself I would not have made something general purpose and it would have taken maybe 30 minutes to do. The second example required no fixing and appears bug free. I asked it to write a python function to take a time trace, calculate and plot the FFT, then apply FFT low pass filtering, and then also plot the filtered time signal vs the original. This is all straight forward numpy code but I don't work with FFTs often and would have had to lookup a bunch of different API docs. Way faster. I have also had it write some c macros for me, since complex C macros can be hard to escape properly and I'm not comfortable with the syntax. Its 100% successful there.

brundolf 4y ago
Yeah, so I think all of these fall under that category I mentioned (the first one may or may not for you, but it would for me because I don't work with Python much): most of the time saved is in looking up a bunch of things to assemble together, not ideating and writing out the logic. I can see this kind of codegen being useful in special situations, but it wouldn't really be useful in my day-to-day work because almost by definition I'm very familiar with the technologies I use every day

ben_w 4y ago

> come up with a way to describe exactly what I want This is the thing: you don't need to be exact. Even very vague gets a long way.

deleted 4y ago
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