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Perhaps people on HN start sensing that successors of Github Copilot will take their programming job. Rightly so.

Personally, I think that in the age of AI programming any notions of code licensing should be abolished. There is no copyright for genes in nature or memes in culture; similarly, these shouldn't be copyright for code.




> Perhaps people on HN start sensing that successors of Github Copilot will take their programming job. Rightly so.

I still think we're a long way from that. Copilot will help write code quicker, but it's not doing anything you couldn't do with a Google search and copy/paste. Once developers move beyond the jr. level, writing code tends to become the least of their worries.

Writing the code is easy, understanding how that code will affect the rest of the system is hard.


Based on the responses I've seen, people have it in their heads that Copilot is a system where you describe what kind of software you want and it finds it on Github and slaps your own license on it.

It's just a smarter tab-completion.


Depends on your definition of "a long way". Some of the GPT3 based code generation demos (which, explicitly, are just that - demos - we aren't shown the limitations of the system during the demo) say that's closer than I think.

https://analyticsindiamag.com/open-ai-gpt-3-code-generator-a... has a bunch of videos of this in action.


That's because the training set had that specific demo, not because copilot imagined up a demo.


> Perhaps people on HN start sensing that successors of Github Copilot will take their programming job. Rightly so.

I feel like this comment misunderstands what a software developer is doing. Copilot isn't going to understand the underlying problem to be solved. It's not going to know about the specific domain and what makes sense and what doesn't.

We're not going to see developers replaced in our lifetime. For that you need actual intelligence - which is very different from the monkey see monkey do AI of today.


The thing is that understanding the domain and thinking out a fairly efficient or elegant solution is something a lot of industry specialist and scientists can do, and only part of programming. Another part is dealing with all the language syntax and specialist lego bits/glue code, and that's something domain specialists tend to be less good at and not enjoy spending time on; it's its own craft.

Having a semi-intelligent monkey that can fetch obvious things off the shelf, build very basic control structures, and do the boring little housekeeping tasks is bad for the craft of programming but very good for the good-enough-solution situation. I can see it having the same impact as cheap and widely available digital cameras; anyone can be a kinda decent photographer now, but if you want to be a professional you're probably going to have to work a lot harder to stand out, whether that's by development of craft, development of narrow technical expertise and fancy equipment, or development of excellent business skills.


The funny thing with "good enough" solutions is that at some point it becomes unmanageable. I've basically spent a good part of my career cleaning up these solutions to make way for scalable, maintainable solutions that don't introduce security holes.

Photography is a good analogy - with everyone having fancy cameras you could think that a photographer is now not necessary. But yes there are still photographers about - they see things that the average person doesn't. The camera doesn't tell them what type of photos to take, what composition the photo should have or what poses a model should have.


You have excellently described the job of business analysts and system architects, but this is not the job of 90% of programmers today, including senior-level. Part of this is already done by other people and doesn't require specific programming skills, hence, at the very least, programmers will lose their privileged position. Another part of it is actually too hard for most people who are currently employed as programmers to do on a decent level (such as meaningfully hacking on Linux kernel).


Memes are absolutely copyrightable, heard of Grumpy Cat?

New genetic sequences are patentable, not copyrightable, but that because of the process involved in creating new genetic sequences more then the genes themselves.

Sure naturally occurring genes aren't patentable, but it's not like we have code growing on trees. So that's a terrible comparison.


The problem with Copilot is, that so far it doesn't seem to be much of an AI and more of an copy-bot. If you are just copying code, you quickly run into copyright issues with your sources. A true AI based on training on open source software would be something different.


Patents on genes actually are a thing. So that example is pretty false. Whether they should be a thing is a separate question, but right now discovery of a gene and it's usefulness can be patented and is done for medical patents.


People aren't happy because Microsoft is exploiting open source. They're training it on open source code and keeping the service for themselves.

If they made the trained model public (and also trained it on private code) the response would be completely different.


>There is no copyright for genes in nature

Since when are humans not a part of nature?




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