I wonder how or if it will impact publicly available code and even open source on a larger scale
GitHub Copilot
341–350 of 1001 posts
Re: GitHub Copilot
#342Earlier 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.
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Re: GitHub Copilot
#343I've been using the alpha for the past 2 weeks, and I'm blown away. Copilot guesses the exact code I want to write about one in ten times, and the rest of the time it suggests something rather good, or completely off. But when it guesses right, it feels like it's reading my mind. It's really like pair programming, even though I'm coding alone. I have a better understanding of my own code, and I tend to give better na…
Pack it all up, boys, programming's over. Hello, AI. Anyone want to hire me to teach your grandma how to use the internet?
Automation has always produced an increase in jobs so far, although sometimes in a disruptive way. I consider this like the switch from instruction-level programming to compiled languages, a level of abstraction added that buys a large increase in productivity and makes projects affordable that weren’t affordable before. If anything this will probably lead to a boom in development work. But there’s a bunch of low skill programmers who can’t do much more than follow project templates and copy paste things. Those people will have to level up or get out.
Re: GitHub Copilot
#344Looks exciting! It is kind of disappointing the AI generated main example on their home page has what appears to be a url encoding bug in it though (in text=${text}, text should be url encoded before being passed to fetch).
Re: GitHub Copilot
#345Hi 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…
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 participate!
Re: GitHub Copilot
#346I'd rate myself as "above-average receptive" to ML-based tooling, but after trying two "AI autocomplete" tools (Kite and TabNine) I've decided it's not for me. The suggestions were usually good, but I found having complex, nondeterministic IDE commands pretty unsettling.
Re: GitHub Copilot
#347Earlier quoted context omitted.
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…
Why would you say it's an error to use a float for currency? I would imagine it's better to use a float for calculations then round when you need to report a value rather than accumulate a bunch of rounding errors while doing computations.
Using float is perfectly OK since using fixed point decimal (or whatever "exact" math operations) will lead to rounding error anyway (what about multiplying a monthly salary by 16/31 (half a month) ?)
The problem with float is that many people don't understand how they work to handle rounding errors correctly.
Now there are some cases where float don't cut it. And big ones. For example, summing a set of numbers (with decimal parts) will usually be screwed if you don't round it. And not many people expect to round the results of additions because they are "simple" operations. So you get errors in the end.
(I have written applications that handle billions of euros with floats and have found just as many rounding errors there as in any COBOL application)
Re: GitHub Copilot
#348I haven't kept up with the adversarial ML field recently, but I wonder how vulnerable these models are to adversarial attacks.
- Could someone deliberately publish poor code to reduce the overall performance of the model?
- Could someone target a specific use case or trigger word by publishing deliberately poor code under similar function definitions?
Re: GitHub Copilot
#349Earlier quoted context omitted.
> - under what license the generated code falls under? Is it even copyrighted? Generally my understand is that to be copyrightable it has to be the output of a human creative process, this doesn't seem to qualify (I am not a lawyer). See also, monkeys can't hold copyright: https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
> Is it even copyrighted? Isn't it subject to the licenses the model was created from, as the learning is basically just an automated transformation of the code, which would be still the original license - as else I could just run some minifier, or some other, more elaborate, code transformation, on some FOSS project, for example the Linux kernel, and relicense it under whatever? Does not sound right to me, but IANAL…
(Not a lawyer, and only at all familiar with US law, definitely uncharted territory)
No, I don't believe it is, at least to the extent that the model isn't just copy and pasting code directly.
Creating the model implicates copyright law, that's creating a derivative work. It's probably fair use (transformative, not competing in the market place, etc), but whether or not it is fair use is github's problem and liability, and only if they didn't have a valid license (which they should have for any open source inputs, since they're not distributing the model).
I think the output of the model is just straight up not copyrighted though. A license is a grant of rights, you don't need to be granted rights to use code that is not copyrighted. Remember you don't sue for a license violation (that's not illegal), you sue for copyright infringement. You can't violate a copyright that doesn't exist in the first place.
Sometimes a "license" is interpreted as a contract rather than a license, in which you agreed to terms and conditions to use the code. But that didn't happen here, you didn't agree to terms and conditions, you weren't even told them, there was no meeting of minds, so that can't be held against you. The "worst case" here (which I doubt is the case - since I doubt this AI implicates any contract-like licenses), is that github violated a contract they agreed to, but I don't think that implicates you, you aren't a party to the contract, there was no meeting of minds, you have a code snippet free of copyright received from github...
Re: GitHub Copilot
#350powered by openai, i'm guessing gpt 3