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GitHub Copilot

copilot.github.com

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Re: GitHub Copilot

#161
post #70
post #37

I wonder if there's any potential for Copilot to suggest malicious code because it's been trained on an open source projects containing intentionally malicious code.

or broken code :D

The averageRuntimeInSeconds example does not check for division by zero so it creates broken code at least 20% of the time based on the examples on the homepage :)

Re: GitHub Copilot

#162
post #71
post #48

Earlier quoted context omitted.

No, a model trained on text covered by a license is not itself covered by the license, unless it explicitly copies the text (you cannot copyright a "style").

But it actually is explicitly copying the text. That's how it works. The training data are massive, and you will get long strings of code that are pulled directly from that training data. It isn't giving you just the style. It may be mashing together several different code examples taking some text from each. That's called "derivative work".

hmm, so let's think this through.

Wouldn't that imply that a person who learned to code on GPLv2 sources wrote writes some more code in that style (including "long strings of code", some of which are clearly not unique to GPL) is writing code that is "born GPLv2"?

I don't think it currently works that way.

Re: GitHub Copilot

#164

So if it was trained using "source code from publicly available sources, including code in public repositories on GitHub." was it also GPLv2? So everything generated also GPLv2?

IMO the closest case is probably the students suing turnitin a number of years ago, which iParadigms (the turnitin maker) won [1].

I think this is definitely a gray area and in some way iParadigms winning (compared to all the cases decided in favour of e.g. the music industry), shows the different yardsticks being used for individuals and companies.

I'm sure we will see more cases about this.

[1] https://www.plagiarismtoday.com/2008/03/25/iparadigms-wins-t...

Re: GitHub Copilot

#165

Earlier quoted context omitted.

do you still go over the generated code line by line and touchup in places where it did not do a good job?

It suggests code line by line, so yes

This is not true - and I've been using copilot for many months :)

It suggests entire blocks of code - but not in every context.

Re: GitHub Copilot

#166
post #88

Calling 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…

> 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…

idk I always find writing code easier than reading code. Perl is a fantastic example of this.

Re: GitHub Copilot

#167

Earlier quoted context omitted.

This is obviously controversial, since we are thinking about how this could displace a large portion of developers. How do you see Copilot being more augmentative than disruptive to the developer ecosystem? Also, how you see it different from regular code completion tools like tabnine.

We think that software development is entering its third wave of productivity change. The first was the creation of tools like compilers, debuggers, garbage collectors, and languages that made developers more productive. The second was open source where a global community of developers came together to build on each other's work. The third revolution will be the use of AI in coding. The problems we spend our days sol…

Let's solve the problem of replacing CEOs next. The above paragraph could have been written by GPT-3 already.

Re: GitHub Copilot

#168
post #8

Should I be impressed that the example parse_expenses.py on the home page doesnt include any error handling and uses a float for currency? This seems like it's going to revolutionize copy and paste programming.

The output is great for a quick one-off script. Maybe if you make the comments look more “enterprise-y”, it’ll go for more careful code?

Re: GitHub Copilot

#169
post #147

Earlier quoted context omitted.

How many jobs have developers helped displace in business and industry? I don't think it's controversial that we become fair game for that same automation process we've been leading.

>How many jobs have developers helped displace in business and industry? I don't think it's controversial that we become fair game for that same automation process we've been leading. historically when has that sort of 'tit-for-tat' style of argument ever been helpful? the correct approach would be "we've observed first hand the problems that we've cause for society, how can we avoid creating such problems for any pe…

> historically when has that sort of 'tit-for-tat' style of argument ever been helpful?

It's not tit-for-tat, it's a wake up call. As in, what exactly do you think we've been doing with our skills and time?

> ""we've observed first hand the problems that we've cause for society"...

But not everyone agrees that this is actually a problem. There was a time when being a blacksmith or a weaver was a very highly paid profession, and as technology improved and the workforce became larger, large wages could no longer be commanded. Of course the exact same thing is going to happen to developers, at least to some extent.

Re: GitHub Copilot

#170
post #48

Earlier quoted context omitted.

No, a model trained on text covered by a license is not itself covered by the license, unless it explicitly copies the text (you cannot copyright a "style").

Well, it probably is explicitly copying at least some subset of the source text - otherwise the code would be syntactically invalid, no?

Strictly speaking, you could train a model which does not contain the original source text (just the underlying language structure and work tokens), and generates ASCII strings which are consistent with the underlying generative model, that are also always valid code. I expect to see code generator models that explicitly generate valid code as part of their generalization capability.
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