Earlier quoted context omitted.
How big/complicated are the functions Copilot is autocompleting for you? I'm thinking perhaps reading 10 potential candidates is actually slower and less instructive than trying to write the thing yourself.
It shows the suggestions line by line, and only shows the best guess. It's not more intrusive than Intellisense. You can actually see all the code blocks Copilot is thinking about if you want to, but that is indeed a distraction.
GitHub Copilot
121–130 of 1001 posts
Re: GitHub Copilot
#122Gigantic caveat. > I agree to these additional telemetry terms as part of the technical preview
"You have zero privacy anyway. Get over it." Scott McNealy, CEO Sun Microsystems, 1999
Perhaps we should ask Scott if he is willing to share his browsing history, his personal photos and his passwords with the rest of us or maybe if I can come into his house?
After all, "You have zero privacy anyway"
Re: GitHub Copilot
#123This is very impressive! OpenAI’s tech opens an ethical Pandora’s box: 1. It’s clear that the raw inputs to all of OpenAI’s outputs originated with real, human creativity. 2. So, in a sense, OpenAI is laundering creativity. It reads in creative works, does complicated (and, yes, groundbreaking) transformations, and produces an output that is hard to trace to any particular source. 3. Yet, isn’t that effectively what…
What are some ethical problems that could emerge from the box? Maybe unfair competition from having very good tools compared to other programmers, or havin irresponsibly shallow understanding of what the produced code does?
Being put out of job by an AI trained on your own code?
It's really the same ethical problem of all automation ... and will be as long as we need a job to fulfill basic needs like food, housing and medical care.
Re: GitHub Copilot
#124Calling 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…
And for those with experience, this will be obvious when reviewing their code. There's only two possibilities -- either copilot will get so good that it won't matter, or code written by copilot will have obvious tells and when someone is over-relying on it to cover up for a lack of knowledge, that will be very clear from repetition of the same sorts of mistakes.
Re: GitHub Copilot
#125Hi 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.
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.
Re: GitHub Copilot
#126So 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?
My guess would be that the model itself (and the training process) could have different legal requirements compared to the code it generates. The code generated by the model is probably sufficiently transformative new work that wouldn't be GPL (it's "fair use"). I suspect there could be issues on the training side, using copyrighted data for training without any form of licensing. Typically ML researchers have a pret…
Re: GitHub Copilot
#127Earlier 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…
How does that apply to countries where Fair Use is not a thing? As in, if you train a model on a fair use basis in the US and I start using the model somewhere else?
Re: GitHub Copilot
#128This is hardly grounds for celebration. Another step in Microsoft's efforts to drive down programmer salaries by expanding the work force. Also, this tool will enable more cheap LOC churn for those gaming performance reviews (not that this is currently difficult, but it will be even easier).
Re: GitHub Copilot
#129Earlier 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?
Take a look at https://karpathy.github.io/2015/05/21/rnn-effectiveness/
At the same time, I would not be surprised if there are outputs that do correspond to the source training data.
Re: GitHub Copilot
#130I wonder how Copilot's suggested snippet compares if the comment is a CS1 homework prompt.