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GitHub Copilot available for JetBrains and Neovim

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Re: GitHub Copilot available for JetBrains and Neovim

#241

Post by throwthere »

jkelleyrtp wrote: post #57

I actually really like Copilot. There tends to be a lot of repetitive code in the world. I primarily write JS, Py, and Rust. Sometimes, I might declare something like a function table, and Copilot will automatically fill in the class definition with everything I defined. I'm not using Copilot to write new algorithms or solve library-specific problems, but it sure is next-level in picking up patterns in a file and pre…

Same experience here. I think a lot of prime are being a little too philosophical about it. Where it shines is small helper functions and predictive boilerplate. It’s more like emmet imo then a pair programmer.

Re: GitHub Copilot available for JetBrains and Neovim

#242

Post by atonalfreerider »

The davinci-codex model that copilot uses also has the capability of translating someone else's code into plain English. This has a great value potential.

Ultimately I'd like to have a conversation with a machine, where I can describe what I want, and the machine can serve me a possible answer, and then I can respond to clarify the idea.

Re: GitHub Copilot available for JetBrains and Neovim

#243

Post by rubyist5eva »

mewse wrote: post #213

I’ve never understood the value proposition for Copilot. In terms of difficulty, writing code is maybe on average a two out of ten. On average, maintaining code you wrote recently is probably a three out of ten in terms of difficulty, and maintaining code somebody else wrote or code from a long time ago probably rises to around a five out of ten. Debugging misbehaving code is probably a seven out of ten or higher. Gi…

This is for outsourcing farms to dump even more garbage code on ignorant founders for pennies.

Re: GitHub Copilot available for JetBrains and Neovim

#244

Post by taormina »

liquidwax wrote: post #234
mewse wrote: post #213

I’ve never understood the value proposition for Copilot. In terms of difficulty, writing code is maybe on average a two out of ten. On average, maintaining code you wrote recently is probably a three out of ten in terms of difficulty, and maintaining code somebody else wrote or code from a long time ago probably rises to around a five out of ten. Debugging misbehaving code is probably a seven out of ten or higher. Gi…

Copilot also optimizes for speed to a degree. It's akin to advanced auto complete. IntelliJ auto-completion is great. As much as it pains to say this, I don't think I will be as effective writing Java in Vim as much as I am with IntelliJ. The key differentiator is the auto complete speed. Copilot I feel is just auto complete on steroids. It may not be perfect yet, but there is definitely a problem it solves.

I mean, why only pick vim or IntelliJ? I get them both with IntelliJ and the plugin.

Re: GitHub Copilot available for JetBrains and Neovim

#245

Post by abecedarius »

knowledge-clay wrote: post #231
abecedarius wrote: post #189

Earlier quoted context omitted.

It's reasonable to worry. - Copilot is qualitatively different from the kinds of automation of programming we've seen before. - It's barely version 1.0 of this kind of thing. Deep learning has been advancing incredibly for a decade and doesn't seem to be slowing down. Researchers also work on things like mathematical problem-solving, which would tie in to "real work" and not just the boilerplate. - In past examples o…

There is a world of difference between what Copilot does and what an engineer does. Imagine reading a design document for a feature and implementing that on a large, years-old codebase, ie, what many engineers do on a daily basis. Copilot isn't even 1 millionth of the way to even beginning to solve that problem, it would require human-level AGI with the capability of understanding human cultural and institutional con…

I'm not so confident this is really different from how a pro Go player would react 10 years ago to the analogous question.

Put it this way: in 5 years will there be an AI that's better than 90% of unassisted working programmers at solving new leetcode-type coding interview questions posed in natural language? Arranging an actual bet is too annoying, but that development in that timeframe doesn't seem unlikely. It might take more than a scaled-up GPT, but as I said, people are working on those other directions too.

In that future, already, the skills you get hired for are different from now (and not just in the COBOL-versus-C sense). Maybe different people with a quite different mix of talents are the ones doing well.

Re: GitHub Copilot available for JetBrains and Neovim

#246

Post by fnoof »

mewse wrote: post #213

I’ve never understood the value proposition for Copilot. In terms of difficulty, writing code is maybe on average a two out of ten. On average, maintaining code you wrote recently is probably a three out of ten in terms of difficulty, and maintaining code somebody else wrote or code from a long time ago probably rises to around a five out of ten. Debugging misbehaving code is probably a seven out of ten or higher. Gi…

I think professional software devs won’t get much value from copilot.

OpenAI’s demo from a few months back showed it as a sort of bridge to convert natural language instructions into APIs calls. Eg converting “make all the headings bold” to calls to a word doc api.

Re: GitHub Copilot available for JetBrains and Neovim

#247

Post by bfung »

crispyalmond wrote: post #218
bastardoperator wrote: post #192

Earlier quoted context omitted.

Wait til stackoverflow sues everyone into oblivion! Letting your intern blindly commit to your code base seems like the bigger issue here. The entire purpose of an internship is to learn and to be guided by professionals, not to be treated as a cheap laborer. You don't hire interns, you train interns. Have you used copilot or are you speculating?

>The entire purpose of an internship is to learn and to be guided by professionals, not to be treated as a cheap laborer. You don't hire interns, you train interns. This has not been my experience. I was dropped into the developer team and expected to know the entire tech stack and was not trained by anyone from the company at any point. Have I been bamboozled??

There’s a huge spectrum of “training”. At least you know you have an expected tech stack. Go learn it and ask questions if things are confusing. Don’t wait to get “trained”.

Re: GitHub Copilot available for JetBrains and Neovim

#248

Post by anigbrowl »

wara23arish wrote: post #142

I have a few questions about copilot. I haven’t gotten a chance to use it yet. Is it irrational that this makes me a little anxious about job security over the longterm? Idk why but this was my initial reaction when learning about this. Given the scenario where copilot and its likes becomes used in a widespread manner. Can it be argued that this might improve productivity but stifle innovation? Im pretty early in my…

I don't think you should worry too much. While it will certainly make it easy for less experienced programmers to catch up with you, it'll probably free you up from a variety of simple but tedious housekeeping tasks and let you concentrate more on designing your program, while also reducing your time to ramp up on stuff that isn't familiar to you.

Re: GitHub Copilot available for JetBrains and Neovim

#249

Post by bennyg »

odonnellryan wrote: post #227
snicker7 wrote: post #197

Earlier quoted context omitted.

Well. Code should be optimized first for correctness, and simple string concatenation will not work for URL params.

It'll certainly work, just seems sloppy.

Plenty of edge cases there (e.g. url encoding), but I don't want to preach to the choir and rabbit hole on this minor detail.

Re: GitHub Copilot available for JetBrains and Neovim

#250

Post by treesprite82 »

ghoward wrote: post #201

I have many thoughts about Copilot, but here are two. First, as much as I don't like the idea of Copilot, it seems to be good for boilerplate code. However, the fact that boilerplate code exists is not because of some natural limitation of code; it exists because our programming languages are subpar at making good abstractions. Here's an example: in Go, there is a lot of `if err == nil` error-handling boilerplate. Ru…

> This means that Google was careful to not make a large amount of copy-righted works publically accessible. Such is not the case for GitHub Copilot in particular Armin Ronacher’s tweet [19]

The fast inverse square root algorithm referenced here didn't originate from Quake and is in hundreds of repositories - many with permissive licenses like WTFPL and many including the same comments. It's not really a large amount of material, either.

GitHub claims they haven't found any "recitations" that appeared fewer than 10 times in the training data. That doesn't mean it's a completely solved issue though, since some code may be in many repositories yet always under non-permissive licenses.

> and I would argue that it will not be the case for ML models in general because all ML models like Copilot will keep suggesting output as long as you ask for it. There is no limit to how much output someone can request. In other words, it is trivial to make such models output a substantial portion of the source code they were trained on.

With the exceptions mentioned above, what you get back from asking for more code won't just be more and more of a particular work. Realistically I think you'd be able to get significantly more from Google Books.

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