AI to write code is cool, but you know what’d be even cooler?
AI for maintaining, upgrading, improving, and fixing code.
After all, devs spend 80%+ of their time doing those things and they’re WAY more painful than writing code imo.
GitHub Copilot
191–200 of 1001 posts
Re: GitHub Copilot
#192Re: GitHub Copilot
#193Hi HN, we've been building GitHub Copilot together with the incredibly talented team at OpenAI for the last year, and we're so excited to be able to show it off today. Hundreds of developers are using it every day internally, and the most common reaction has been the head exploding emoji. If the technical preview goes well, we'll plan to scale this up as a paid product at some point in the future.
What do you think about this being overall detrimental to code quality as it allows people to just blindly accept completions without really understanding the generated code. Similar to copy-and-paste coding.
The first example parse_expenses.py uses a float for currency - that seems to be a pretty big error that's being overlooked along with other minor issues around no error handling.
I would say the quality of the generated code in parse_expenses.py is not very high, certainly not for the banner example.
EDIT - I just noticed Github reordered the examples on copilot.github.com in order to bury the issues with parse_expenses.py for now. I guess I got my answer.
Re: GitHub Copilot
#194Earlier quoted context omitted.
> If you need to go through the suggested code to ensure it's correct, you may as well write it yourself? Not really. People are generally far faster at reading something and evaluating whether it's correct, than at writing something. In the same way it's faster to read a book than to write one. Not to mention the time it takes typing, fixing typos, etc. So this could genuinely be a huge timesaver if it helpful enoug…
I completely disagree with you. Reading code for correctness is difficult and not something most people do well at all. Reading code and reading for correctness are not the same, and most developers can write code a lot faster than they can verify it.
That’s what a REPL and automated tests are for.
Re: GitHub Copilot
#195[deleted]
Re: GitHub Copilot
#196Earlier quoted context omitted.
Might this end up putting GPL code into projects with an incompatible license?
It shouldn't do that, and we are taking steps to avoid reciting training data in the output: https://copilot.github.com/#faq-does-github-copilot-recite-c... https://docs.github.com/en/early-access/github/copilot/resea... In terms of the permissibility of training on public code, the jurisprudence here – broadly relied upon by the machine learning community – is that training ML models is fair use. We are certain this…
You just shared a URL that says "Please do not share this URL publicly".
Re: GitHub Copilot
#197Hi HN, we've been building GitHub Copilot together with the incredibly talented team at OpenAI for the last year, and we're so excited to be able to show it off today. Hundreds of developers are using it every day internally, and the most common reaction has been the head exploding emoji. If the technical preview goes well, we'll plan to scale this up as a paid product at some point in the future.
Lots of questions:
- the generated code by AI belongs to me or GitHub?
- under what license the generated code falls under?
- if generated code becomes the reason for infringment, who gets the blame or legal action?
- how can anyone prove the code was actually generated by Copilot and not the project owner?
- if a project member does not agree with the usage of Copilot, what should we do as a team?
- can Copilot copy code from other projects and use that excerpt code?
- if yes, *WHY* ?!
- who is going to deal with legalese for something he or she was not responsible in the first place?
- what about conflicts of interest?
- can GitHub guarantee that Copilot won't use proprietary code excerpts in FOSS-ed projects that could lead to new "Google vs Oracle" API cases?Re: GitHub Copilot
#198Calling it now, there will be a "Copilot considered harmful" post. If you need to go through the suggested code to ensure it's correct, you may as well write it yourself? If you glance at it and it looks about right, you can potentially overlook bugs or edge cases, you'll lose confidence in your own code since you didn't properly conceptualise it yourself. Potentially for newer developers it robs them of active exper…
Think of it as a junior dev working under you and doing the grunt work of typing in your ideas. Sometimes he can StackOverflow a better snippet than you can write on your own, you will probably learn a bit from it, but it won't surprise you.
It is no different from a code review of another perhaps junior dev and only doing adding finishing touches.
There is plenty of boilerplate you have to write, Intellisense/ Auotfill only goes so far, this is next step in the evolution. Sure it is not perfect but if i can express my ideas faster, why not.
Also It is a very probably poor tool for new devs, they won't know that suggestion maybe not the best and probably won't ignore it when it is wrong as they won't know any better.
Re: GitHub Copilot
#199What could go wrong? Expecting software to become even shittier.
Re: GitHub Copilot
#200I'm primarily an R and SQL user, excited to try this out on some fun data analyses.
How did you construct the Copilot? Did you use a learning approach based on data from actual pair-programming sessions? Or did you take tons of code as your input and use that to suggest next methods based on input code?
I learned a ton whenever I pair programmed, but now I'm at a small company so I'm looking for fun ways to learn new methods :)