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GitHub Copilot

copilot.github.com

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Re: GitHub Copilot

#811

Post by devetec »

not2b wrote: post #71
dekhn wrote: 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".

If you learn programming from Stack Overflow and Github, and then repeat something that you learned over your time at reading, that's not just copying text. That's having learned the text. You could say the human brain is mashing together several different code examples, taking some text from each.

Re: GitHub Copilot

#813

Post by ablekh »

I certainly see the value in solutions like GitHub Copilot (if implemented well), at least, from three perspectives: a) 𝐩𝐞𝐝𝐚𝐠𝐨𝐠𝐢𝐜𝐚𝐥 (by allowing developers, especially beginners, to see the diversity in different approaches to potential solutions for specific problems), b) 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐛𝐞𝐬𝐭 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 [of course, it should be used with care and, generally, the quality of relevant suggestions from this angle is still TBD] and c) 𝐢𝐦𝐩𝐫𝐨𝐯𝐢𝐧𝐠 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲 (this is especially relevant for programming languages and frameworks with lots of boilerplate code - e.g., C#/.NET, Java). Spending much less time on typing typically very verbose boilerplate code will give software developers much more time to spend on truly valuable and important activities, such as problem solving, architecting, collaborating.

Re: GitHub Copilot

#814

Post by mtnygard »

kopos wrote: post #801
FreeSpeech wrote: post #680

Earlier quoted context omitted.

Has anyone used Copilot with a more succinct language? It appears to only automate boilerplate and rudimentary patterns, which while useful in repetitive low signal to noise ratio languages like React or Java, sounds less appealing if you're writing Clojure.

Or the converse? If Copilot is as good as it gets but only for some languages, won’t it influence what languages will be chosen by devs or companies?

Indeed, I could imagine it becoming more difficult to adopt a language that doesn't already have a large corpus to train on.

Re: GitHub Copilot

#815

Post by Tainnor »

wiz21c wrote: post #347
as300 wrote: post #211

Earlier quoted context omitted.

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…

No, exact precision arithmetic can do that 16/31 example without loss of precision:

  from fractions import Fraction
  
  # salary is $3210.55
  salary = Fraction(321055,100)
  monthlyRate = Fraction(16,31)

  print(salary*monthlyRate)
This will give you an exact result. Now, at some point you'll have to round to the nearest cent (or whatever), true. However, you don't have to round between individual calculations, hence rounding errors cannot accumulate and propagate.

The propagation of errors is the main challenge with floating point numbers (regardless of which base you use). The theory is well understood (in the sense that we can analyse an algorithm and predict upper bounds on the relative error), but not necessarily intuitive and easy to get wrong.

Decimal floating-point circumvents the issue by just not introducing errors at all: money can be represented exactly with decimal floating point (barring very exotic currencies), therefore errors also can't propagate. Exact arithmetic takes the other approach where computations are exact no matter what (but this comes at other costs, e.g. speed and the inability to use transcendental functions such as exp).

For binary floating point, that doesn't work. It introduces errors immediately since it can't represent money well and these errors may propagate easily.

Re: GitHub Copilot

#816

Post by rjzzleep »

kopos wrote: post #801
FreeSpeech wrote: post #680

Earlier quoted context omitted.

Has anyone used Copilot with a more succinct language? It appears to only automate boilerplate and rudimentary patterns, which while useful in repetitive low signal to noise ratio languages like React or Java, sounds less appealing if you're writing Clojure.

Or the converse? If Copilot is as good as it gets but only for some languages, won’t it influence what languages will be chosen by devs or companies?

I really wonder sometimes if Java would never have made it that far if it wasn’t for eclipse and later IntelliJ.

Re: GitHub Copilot

#818

Post by sennight »

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.

huh... I've found that people who tend to describe their occupation as "knowledge work" are the most blind to the fact that white collar jobs are the first to get optimized away. Lawyers are going to have a really bad time after somebody manages to bridge NLP and formal logic. No, it won't result in a Lawyerbot-2000 - it will result in software that enables lawyers to do orders of magnitude more work of a higher quality. What do you think that does to a labor market? It shrinks it. That or people fill the labor glut with new, cheaper, lawsuits...

Re: GitHub Copilot

#819

Post by gutino »

iwintermute wrote: post #21

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?

Developers Human brain are also trained with propietary code bases, then when they quit and go elswere , they program using knowledge learned previously, yet you do not sue them.

Re: GitHub Copilot

#820

Post by MichaelMoser123 »

sennight wrote: post #818
anthropodie wrote: post #335

Earlier quoted context omitted.

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.

huh... I've found that people who tend to describe their occupation as "knowledge work" are the most blind to the fact that white collar jobs are the first to get optimized away. Lawyers are going to have a really bad time after somebody manages to bridge NLP and formal logic. No, it won't result in a Lawyerbot-2000 - it will result in software that enables lawyers to do orders of magnitude more work of a higher qual…

i don't think that people will ever fully trust an AI lawyer, given all the possible legal consquences of a misunderstanding between the AI and the client. You could literally go to jail because of a bug/misunderstanding due to an ambiguous term (this might make a good sci-fi story ...)

But yes, getting some kind of legal opinion will probably be cheaper with an AI.

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