this post was submitted on 20 Oct 2023
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I thought it was copy and pasting from stack overflow
Now a days it's:
ChatGPT has taught me so much basic programming I should have learned years ago. Don't know if I'll remember any of it since Ill just end up pasting my almost working stuff into ChatGPT again once I'm stuck.
^^^ How skynet was born, ChatGPT injecting subroutines copied by lackadaisical programmers copying and pasting without checking
Oh I'm reading and making sure I understand everything. I usually write the suggestions into my code myself to try to get it into my fingers. But it is usually basic stuff I haven't done very often I struggle with. Like building a JSON as an object by adding each part step by step and serializing every input properly, instead of just building the JSON string by hand.
Chatgpt is good for code reviews. I wouldn't trust it for making code though.
Are there any other LLM interfaces or co-pilot programming tools you'd recommend over ChatGPT, or wouldn't you trust LLMs in general?
As I see it, since we can keep iterating, reviewing, rewriting prompts, and even use tools like autogen to let multiple LLMs interact to solve a problem on our behalf, your take is somehow only diggin' the surface.
Mostly, its my own personal choice / preference.
When I see chatgpt spun up code, sometimes its rock solid. Sometimes it uses weird logic that is hard to follow. I prefer it to review my code, rather than review its.
I'm kind of partial to how military concepts use cases for ai. Like anything that can do damage or complex tasks must be done by a human. Mediocre tasks, I can see a use for it.
Like for instance, write a code to automate scheduling jobs to backup multiple systems using this fileset to backup or skip I'd feel OK to let ai do. They should all be basically the same. But to script code that is critical to infrastructure and/or complex I feel it is not the right tool to use.
Edit: all LLMs are basically the same imo. The github one might have access to more code though, idk never used it. If it does look at private repos, then I'd say it would be better, but honestly I think they're about the same.
Don't you think it's just a question of time before it's becoming good enough or better than us at some of these tasks? I do. With better training data, more parameters, better quantization, and now even memory management with memGPT, I see some very interesting evolutions becoming possible.
To me, saying "all LLMs are the same", sounds like saying "all humans are the same", to which I strongly disagree. Different people are good at different things. Otherwise, there'd be no need to hire any specialized workers.
Military usecases is a big ethical discussion. Autonomous drones sound pretty scary, at least as long as the technologies are not fully understood. Many people would probably agree that humans should always stay in control when serious damage could be done. However, many are ok with self-driving cars etc. There are many answers to be found in this regard, but I'm not sure this thread is the place to find them... However, I'd still like to hear if you have any thoughts to add on autonomous machines.
In my experience, it tends to have difficulties with restrictions, and will attempt to use the normal method for things no matter what
Should I feel bad if I feel referenced?
Edit: No. Not really, and neither does anyone else reading this. It's stupid to feel bad about what an absolute stranger says on the internet.
If that's literally all you do, then yes. If not, you just know your tools.
Not so, I code by myself and when I have a problem I ask ChatGPT but I do not say "do everything for me".
Look at John Henry over here
What?
I'm actually impressed how aptly that reference applies.
The legend of John Henry is that he beat a steam engine at the task of drilling through a mountain. John and his assistant (a shaker) had the advantage of being able to finely tune how the steel driver was placed, struck, and chips of rock moved out of the way. Contrast that with how the steam engine drill just rotely brute-force drilled, but got clogged by the resulting rock chips and could drill no more.
So the moral is the humans beat out the machine due to being able to finesse the situation, even though intuitively a machine should have been able to prevail due to its superior raw strength.
Eventually, but it starts with Googling and trying a bunch of other example code and failing miserably.
Don't forget rewriting the entire thing a few times until you find a library that actually does what you need it to.
Hahhaa yes