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GitHub Copilot

copilot.github.com

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Re: GitHub Copilot

#451

Post by qqqwerty »

anthropodie wrote: post #335
asdfman123 wrote: post #309

Earlier quoted context omitted.

Pack it all up, boys, programming's over. Hello, AI. Anyone want to hire me to teach your grandma how to use the internet?

Few days back, Sam Altman tweeted this "Prediction: AI will cause the price of work that can happen in front of a computer to decrease much faster than the price of work that happens in the physical world. This is the opposite of what most people (including me) expected, and will have strange effects" And I was like yeah I gotta start preparing for next decade.

We went through the same hype cycle with self driving cars. We are now ~15 years out from the DARPA challenges and to date exactly 0 drivers have been replaced by AI.

It is certainly impressive to see how much the GPT models have improved. But the devil is in the last 10%. If you can create an AI that writes perfectly functional python code, but that same AI does not know how to upgrade an EC2 instance when the application starts hitting memory limits, then you haven't really replaced engineers, you have just given them more time to browse hacker news.

Re: GitHub Copilot

#452

Post by UnFleshedOne »

staticassertion wrote: post #437
inimino wrote: post #385

I'm amazed to see how positive the overall response is to this idea. Almost as if programmers think that writing programs is the worst part of the job and ready to be automated away. As someone more aligned with the Dijkstra perspective, this seems to me like one of the single worst ideas I've ever seen in this domain. We already have IDEs and other tools leading to an increase in boilerplate and the acceptance of it…

> Almost as if programmers think that writing programs is the worst part of the job and ready to be automated away. writing the programs is definitely boring garbage work. Typing is so slow and annoying - hence autocomplete being a standard tool. This is, to me, just fancy autocomplete. > to an increase in boilerplate and the acceptance of it because they make it easier to manage. Boilerplate optimizes for the right…

Boilerplate is only easier to read and analyze if you can be sure it is consistent, so you can tune it out. Usually though, there is this one getter method that is not quite like the others and you literally will not see the difference until it bites you.

We'll need more IDE enhancements, to highlight interesting pieces and desaturate standard boilerplate...

Re: GitHub Copilot

#453

Post by davidthewatson »

inimino wrote: post #385

I'm amazed to see how positive the overall response is to this idea. Almost as if programmers think that writing programs is the worst part of the job and ready to be automated away. As someone more aligned with the Dijkstra perspective, this seems to me like one of the single worst ideas I've ever seen in this domain. We already have IDEs and other tools leading to an increase in boilerplate and the acceptance of it…

Cargo cults concerned me too but I realized that cargo-cult programming flourishes when it's enabled by a culture that doesn't care how the sausage is made. If the culture seeks full stack truth, it's not likely to get fooled by bad generated code, no matter whether it's generated by copy/paste, metaprogramming, or AI.

I'd love to know what Donald Knuth thinks given the history of literate programming.

Re: GitHub Copilot

#454

Post by throwaway675309 »

inimino wrote: post #385

I'm amazed to see how positive the overall response is to this idea. Almost as if programmers think that writing programs is the worst part of the job and ready to be automated away. As someone more aligned with the Dijkstra perspective, this seems to me like one of the single worst ideas I've ever seen in this domain. We already have IDEs and other tools leading to an increase in boilerplate and the acceptance of it…

I mean you say this, but you and most likely the majority of programmers rely on dozens of repositories, packages and libraries with likely zero deep understanding of it (and at the very least haven't read the source code of ) so I don't really understand the difference here.

The advantage of something like this is that instead of having to go to stack overflow or any number of reference sites and copy pasta it can just happen automatically without me having to leave my IDE.

The enjoyable part of programming for me is not typing the Ajax post boilerplate bullcrap for the millionth time, it's the high-level design and abstract reasoning.

Re: GitHub Copilot

#455

Post by dgb23 »

shadowgovt wrote: post #289
dgb23 wrote: post #188

Earlier quoted context omitted.

I honestly think this is solving a real problem with commonly used languages and their lack of syntax abstraction and expressiveness. I can imagine this being very useful in helping to type out what I consider to be „mechanical noise“: Things that you have to type out to satisfy an expression rather than to convey semantics. A good example of how this type of noise manifests: Observe two programmers, both being simil…

It is even entirely possible that this approach hits a middle-ground that serves the corporate software-development space better than highly-flexible languages. The difficulty with high flexibility is that the expressions become very domain-specific very quickly, creating the challenge of learning the new abstractions. So one isn't just a LISP developer, one knows how to write in the specific forest of macros that ha…

I’ve seen macro heavy code that is very semantic and declarative. It’s a powerful tool, so it is natural that people need to learn and fail until they use it well.

Re: GitHub Copilot

#456

Post by smoldesu »

I'm willing to go all-in on something like this, only if I can get a promise that this will be an open project as time goes on. I'm not a fan of all of the "commercial" talk in this... if OpenAI is involved, and most of this can run locally, why can't it be fully open source?

Re: GitHub Copilot

#457

Post by novok »

inimino wrote: post #385

I'm amazed to see how positive the overall response is to this idea. Almost as if programmers think that writing programs is the worst part of the job and ready to be automated away. As someone more aligned with the Dijkstra perspective, this seems to me like one of the single worst ideas I've ever seen in this domain. We already have IDEs and other tools leading to an increase in boilerplate and the acceptance of it…

I've used tabnine for a while, and it's mostly just been a faster executing normal autocomplete, with a %90 accuracy rate. It's a tradeoff. It didn't have the large snippet behavior in my usage like this new one although.

Re: GitHub Copilot

#459

Post by joepie91_ »

natfriedman wrote: post #345
stefanos82 wrote: post #197

Earlier quoted context omitted.

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…

In general: (1) training ML systems on public data is fair use (2) the output belongs to the operator, just like with a compiler. On the training question specifically, you can find OpenAI's position, as submitted to the USPTO here: https://www.uspto.gov/sites/default/files/documents/OpenAI_R... We expect that IP and AI will be an interesting policy discussion around the world in the coming years, and we're eager to…

> training ML systems on public data is fair use

Uh, I very much doubt that. Is there any actual precedent on this?

> We expect that IP and AI will be an interesting policy discussion around the world in the coming years, and we're eager to participate!

But apparently not eager enough to have this discussion with the community before deciding to train your proprietary for-profit system on billions of lines of code that undoubtedly are not all under CC0 or similar no-attribution-required licenses.

I don't see attribution anywhere. To me, this just looks like yet another case of appropriating the public commons.

Re: GitHub Copilot

#460

Post by hartator »

How does it compare to Tabnine?

I really like thar Tabnine train against your own codebase and suggest things based on it. It’s crazy accurate and smart a surprising amount of time.

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